How to Build a Logic Model

A logic model is a one-page map of how a project turns resources into results: situation, inputs, activities, outputs, short-term, intermediate, and long-term outcomes, and impact. Build one backward — start from the outcome you intend, then work left to the activities that could plausibly produce it.

Key takeaways

• A logic model shows what a project will do and produce.
• Build it right to left, from intended outcome back to activities.
• Every adjacent pair of columns must survive an if-then test.
• Assumptions and external factors belong on the page, not in your head.
• The logic model is the skeleton for objectives, evaluation, and reporting.

What is a logic model?

A logic model is a framework that names the working parts of a project and describes how those parts are expected to produce results. The U.S. Department of Education defines a logic model as “a framework that identifies key project components of the proposed project (i.e., the active ‘ingredients’ that are hypothesized to be critical to achieving the relevant outcomes)” (34 CFR 77.1).

The most widely used construction guide is the W.K. Kellogg Foundation’s Logic Model Development Guide, which organizes the model into five components — resources, activities, outputs, outcomes, and impact (W.K. Kellogg Foundation, 2004). The National Institute of Justice describes the same artifact functionally: a logic model “visually depicts how a program is expected to work and achieve its goals, specifying the program’s inputs, activities, outputs and outcomes” (NIJ, 2015). Most funders in the evidence, evaluation, and data space work from some variant of that structure.

A logic model is not a work plan and not a budget. A logic model is a causal claim rendered as a diagram: given these resources, these activities, at this dose, this much change follows. The Centers for Disease Control and Prevention treats the logic model as part of describing the program, which then anchors the evaluation questions that follow (CDC Program Evaluation Framework, 2024). Federal reviewers score it directly: one of the Department of Education’s general selection criteria asks reviewers to judge “the quality of the logic model or other conceptual framework underlying the proposed project, including how inputs are related to outcomes” (34 CFR 75.210).

What are the columns of a logic model?

A logic model has eight parts, though many templates collapse or rename some of them. There are eight elements a complete logic model carries:

• Situation or problem. The condition the project exists to change, with the data that documents it. Pull from the same evidence you use in the public data sources for needs statements.
• Inputs or resources. Kellogg defines resources as “the human, financial, organizational, and community resources a program has available to direct toward doing the work.”
• Activities. Kellogg: “the processes, tools, events, technology, and actions that are an intentional part of the program implementation.”
• Outputs. Kellogg: “the direct products of program activities,” including “types, levels and targets of services to be delivered by the program.”
• Short-term outcomes. Learning changes — knowledge, awareness, attitude, skill — among the people the project reached (PCAR, 2018).
• Intermediate outcomes. Action changes: behavior, practice, decision-making, or policy adoption that follow from the short-term changes.
• Long-term outcomes. Condition changes — social, economic, civic, or environmental status. The result the funder is actually buying.
• Impact. Kellogg reserves impact for “fundamental intended or unintended change occurring in organizations, communities or systems,” on a horizon of roughly seven to ten years.

The Urban Institute calls the same diagram an outcome sequence chart, running from inputs through activities and outputs to intermediate and then end outcomes (Lampkin and Hatry, Urban Institute). Two elements sit underneath the columns rather than inside them, and most applicants omit both. Assumptions are the beliefs that must hold for the chain to work — that data arrive fast enough to act on, that staff can be hired in this labor market, that participants can reach the site. External factors are the forces outside the project that could break the chain regardless of execution quality.

Adaptations of the Kellogg and CDC models treat program context and external pressures as a distinct sixth element (Tennessee Office of Evidence and Impact). Naming assumptions is a rigor signal. Unnamed assumptions are what evaluations discover expensively, in year two.

Why should a logic model be built right to left?

Build a logic model backward because the outcome is the only fixed point. Starting from the left — from the activities an organization already runs — produces a model that justifies existing work rather than one that reaches a result. Starting from the right forces the harder question: what would actually have to happen for this change to occur?

The backward method comes from theory-of-change practice, where planners begin with the long-term outcome and work back toward the earliest changes required. As the ActKnowledge basics guide puts it, backward mapping “is the opposite of how we usually think about planning, because it starts with asking ‘What preconditions must exist for the long-term outcome to be reached?’ rather than with ‘What activities can we be doing to advance our goals?’” (Theory of Change Basics). The Community Tool Box describes the same technique as repeatedly asking “but how?” until the answers reach something the program can do (Community Tool Box, University of Kansas).

Backward construction has a practical payoff at review time. A logic model built right to left rarely contains orphan activities — work with no outcome attached — because every activity earned its place by answering a precondition. A logic model built left to right almost always does, and reviewers read orphan activities as budget padding. Write the logic model backward; present it forward.

How do you build a logic model, step by step?

Building a logic model takes seven passes, and the order matters more than the template. There are seven steps:

1. Write the long-term outcome first, in the funder’s own vocabulary, drawn from the purpose statement of the notice of funding opportunity. If the outcome does not appear in the funder’s language somewhere, the logic model is aimed at the wrong target.
2. Work backward through preconditions. For the long-term outcome, ask what must be true first. Repeat for each answer until the preconditions reach something the project can plausibly affect within the period of performance.
3. Name the activity that produces each precondition. In Department of Education competitions, use the regulatory term: a project component is “an activity, strategy, intervention, process, product, practice, or policy included in a project” (34 CFR 77.1).
4. Specify dose for every activity. How many, how often, how long, delivered by whom, to whom. Dose is where reviewers catch fantasy — a caseload of 1:45 and a caseload of 1:200 are different programs wearing the same label.
5. Convert activities into countable outputs, each with a target. Outputs are service-delivery units, not benefits. The distinction between outputs and outcomes decides how the whole right side of the model reads.
6. Attach an indicator and a data source to every outcome box. A box with no measure is decoration. Either measure it or delete it.
7. Write the assumptions and external factors underneath, then read the model backward asking “is this sufficient?” and forward asking “is this necessary?” Cut whatever fails both tests.

Build it with other people. Kellogg describes refinement as “an iterative or repeating process that allows participants to make changes based on consensus-building and a logical process rather than on personalities, politics, or ideology.” A logic model drafted alone at midnight encodes one person’s assumptions and no one else’s objections.

What does a completed logic model look like?

A completed logic model reads as a single connected chain, with a measure attached to every result box. The example below is illustrative — a hypothetical healthcare-support workforce program run by a community-based organization with a community college partner. The figures are invented to show the arithmetic of a model, not drawn from a real program.

Logic model element	Contents for the example program
Situation	Regional demand for healthcare support occupations exceeds local credential production; adults without credentials are concentrated in low-wage service work
Inputs	Three-year grant; two navigators; one instructor; college MOU; employer advisory panel; existing student information system; external evaluator
Activities	Cohort-based certified nursing assistant training, 120 contact hours; weekly navigation contacts at 1:40 caseload; paid clinical placement; employer-hosted hiring events
Outputs	Six cohorts delivered; 180 adults enrolled; 4,200 navigation contacts logged; 150 clinical placements filled; 12 hiring events held
Short-term outcomes	Credential exam pass rate rises from a documented cohort baseline; participants report increased job-search self-efficacy at course end
Intermediate outcomes	Employment in a healthcare support occupation within 90 days of completion; employer-reported retention at 6 months
Long-term outcomes	Median participant earnings rise relative to pre-enrollment wage records; sustained employment at four quarters after exit
Impact	Regional healthcare support vacancy rate narrows; fewer working-age adults in the service area remain below the self-sufficiency wage
Assumptions	Clinical placement slots remain available at partner sites; wage-record data sharing is executed before enrollment begins; participants have reliable transportation to clinical sites
External factors	Employer hiring freezes; changes to state certification requirements; loss of childcare subsidy funding in the service area

Notice what the assumptions row does. The transportation assumption is the one most likely to fail, and naming it lets the project design a mitigation — and lets the evaluator measure whether the mitigation worked. A logic model that hides its weakest link is less useful than one that points at it.

How detailed should a logic model be?

A logic model should be detailed enough that a reviewer can trace a single participant through it, and no more detailed than that. The working test is the if-then test applied to adjacent columns: if these resources, then these activities; if these activities at this dose, then these outputs; if these outputs, then this short-term change.

Kellogg states the chain plainly: “If you have access to them, then you can use them to accomplish your planned activities. If you accomplish your planned activities, then you will hopefully deliver the amount of product and/or service that you intended” (W.K. Kellogg Foundation, 2004). Where an if-then link reads as a leap, the logic model is missing a box, and a reviewer will find the gap faster than the author will.

Granularity has a ceiling set by the page limit. Most funders allot one page, often in an appendix. Three techniques keep a logic model legible inside that constraint: group activities into three to five named components rather than listing every task, put dose in the activity cell as a parenthetical rather than a separate column, and move assumptions and external factors into two short rows at the bottom. There is no correct template — a model built for a management plan will look different from one built for a funder’s reviewer.

How does a logic model shape the rest of a proposal?

A logic model is the structural skeleton for four later sections, and reviewers check the alignment. Objectives are the outcome boxes restated as measurable commitments with baselines and targets — which is why goals, objectives, and activities should be drafted after the model, never before.

The evaluation plan is the logic model with a measurement column bolted on. The distinction the model has to support is the one the CDC draws between performance measurement, “the ongoing monitoring and reporting of program accomplishments,” and program evaluation, which “helps you to identify the reason behind these changes” (CDC Approach to Program Evaluation).

Guidance developed for federal grant applicants is explicit that evaluation questions, data sources, measures, and analysis procedures should each align to a named logic-model element, and that the wording in the evaluation plan should match the wording in the model. Building the evaluation plan from the model prevents the most common structural failure: boxes that appear in no measure, and measures that appear in no box.

The budget traces back to the inputs column. Every input that costs money must appear as a budget line, and every budget line should trace to an input or an activity. Reviewers routinely flag a narrative describing a full-time coordinator with no corresponding personnel line.

Post-award reporting inherits whatever the model promised. Federal performance reporting compares accomplishments against the objectives established for the award (2 CFR 200.329), so the outcome boxes drafted during proposal week become the rows of a report filed years later. Draft them as things you can actually count.

What goes wrong in a logic model?

Six failures account for most of the points lost on a logic model, and reviewers spot all six quickly. There are six recurring problems:

• Outputs sitting in the outcomes column. “500 people served” is a count of delivery, not a change in anyone. Misplacing it is the single most common first-time error.
• Orphan boxes. An activity with no outcome downstream, or an outcome with no activity upstream, signals a model assembled rather than reasoned.
• No dose. Activities described without frequency, duration, or caseload cannot be evaluated for fidelity and cannot be costed.
• Missing assumptions. A model with no assumptions row implies either that nothing could go wrong or that no one asked.
• Long-term outcomes that cannot move inside the period of performance. A three-year grant whose only outcome is a five-year lagging indicator is structurally unable to demonstrate progress. Pair every lagging measure with a leading one.
• A model that contradicts the narrative. Different verbs, different populations, different numbers in the model than in the project design section. Reviewers read them side by side.

The underlying discipline is stated best by Carol Weiss, quoted in the Kellogg guide: “A program is a theory and an evaluation is its test.” A logic model that cannot be tested is not a theory. It is a picture.

Frequently asked questions

Is a logic model required in every grant application?

No. Human-services and education funders commonly require an explicit logic model, and it is named in the Department of Education’s selection criteria (34 CFR 75.210). Research funders such as NIH and NSF usually expect the equivalent reasoning inside the approach or project description rather than as a separate diagram.

Does a logic model go in the narrative or an appendix?

Follow the notice of funding opportunity. Many competitions place the logic model in an appendix that does not count against the narrative page limit, which is a strong argument for producing a clean one-page graphic. When placement is unspecified, put a compact model in the narrative near the project design section.

What is the difference between a logic model and a theory of action?

Federal education regulations treat the two terms as equivalent, defining “logic model (also referred to as theory of action)” in a single entry (34 CFR 77.1). Some funders use “theory of action” to signal a stronger emphasis on causal reasoning. Read the notice of funding opportunity’s usage rather than the textbook’s.

How many outcomes should a logic model contain?

Enough to cover the objectives and no more. Most competitive models carry two to four long-term outcomes, each with one or two short-term and intermediate precursors. Every outcome adds a measurement obligation, a data source, and a cost, so an outcome you cannot afford to measure should not be in the model.

Should the logic model include activities the grant does not fund?

Generally no, though partner-funded activities that are preconditions for your outcomes can appear in a shaded or bracketed form. Work outside the grant belongs in the broader causal argument. A logic model is an operational depiction of what this award buys.

Related topics

• Evidence, Evaluation, and Data — the hub for proving a project will work, and then proving it did
• Outputs, Outcomes, and Impact
• Performance Measurement and Indicators
• Levels of Evidence in Grant Funding
• Grant Reporting Requirements

Sources

1. U.S. Department of Education. 34 CFR 77.1 — Definitions that apply to all Department programs. Legal Information Institute, Cornell Law School. https://www.law.cornell.edu/cfr/text/34/77.1 (accessed 2026-08-11)
2. U.S. Department of Education. 34 CFR 75.210 — General selection criteria. Legal Information Institute, Cornell Law School. https://www.law.cornell.edu/cfr/text/34/75.210 (accessed 2026-08-11)
3. W.K. Kellogg Foundation. Logic Model Development Guide. 2004. https://www.naccho.org/uploads/downloadable-resources/Programs/Public-Health-Infrastructure/KelloggLogicModelGuide_161122_162808.pdf (accessed 2026-08-11)
4. Kidder, D. P., Fierro, L. A., Luna, E., et al. CDC Program Evaluation Framework, 2024. MMWR Recommendations and Reports 73(RR-6):1–37. https://www.cdc.gov/mmwr/volumes/73/rr/rr7306a1.htm (accessed 2026-08-11)
5. Centers for Disease Control and Prevention. CDC Approach to Program Evaluation. https://www.cdc.gov/evaluation/php/about/index.html (accessed 2026-08-11)
6. Taplin, D. H., and Clark, H. Theory of Change Basics: A Primer on Theory of Change. ActKnowledge / Center for Theory of Change. https://www.theoryofchange.org/wp-content/uploads/toco_library/pdf/ToCBasics.pdf (accessed 2026-08-11)
7. Community Tool Box, Center for Community Health and Development, University of Kansas. Developing a Logic Model or Theory of Change. https://ctb.ku.edu/en/table-of-contents/overview/models-for-community-health-and-development/logic-model-development/main (accessed 2026-08-11)
8. Tennessee Office of Evidence and Impact. Logic Models. Hosted by Results for America. https://results4america.org/wp-content/uploads/2019/12/4-Logic-Models.pdf (accessed 2026-08-11)
9. Pennsylvania Coalition Against Rape. Theory of Change and Logic Models. 2018. https://pcar.org/sites/default/files/resource-pdfs/tab_2018_logic_models_508.pdf (accessed 2026-08-11)
10. Office of Management and Budget. 2 CFR 200.329 — Monitoring and reporting program performance. Legal Information Institute, Cornell Law School. https://www.law.cornell.edu/cfr/text/2/200.329 (accessed 2026-08-11)
11. National Institute of Justice. Plan for Program Evaluation from the Start. March 1, 2015. https://nij.ojp.gov/topics/articles/plan-program-evaluation-start (accessed 2026-08-11)
12. Lampkin, L. M., and Hatry, H. P. Key Steps in Outcome Management. Urban Institute. https://www.urban.org/sites/default/files/publication/42736/310776-Key-Steps-in-Outcome-Management.PDF (accessed 2026-08-11)