10 Decision Tree Examples You Can Copy (+ How to Make One)

A decision tree turns a fuzzy judgment call into a series of small yes/no questions. Instead of debating "should we hire this person?" in the abstract, you walk a path: meets the bar on skills? → passed the work sample? → team fit confirmed? → offer. That structure is why decision trees show up everywhere from support desks to boardrooms.

This page collects decision tree examples you can copy directly, each with a short text prompt you can paste into an AI flow chart maker to generate an editable version in seconds.

What is a decision tree diagram?

A decision tree diagram is a branching chart that starts from one question at the root and splits at every decision point until each path ends in an outcome. Three elements do all the work:

• Decision nodes — the questions, usually drawn as the branching points.
• Branches — the possible answers (most trees stick to yes/no to stay readable).
• Leaves — the outcomes at the end of each path: approve, reject, escalate, buy, wait.

If a chart has one starting question and every path ends in a clear outcome, it's a decision tree. (Trees with loops back to earlier steps are really flowcharts — see our flow chart examples for those.)

Business decision tree examples

1. Hiring screen

Resume meets requirements? → no: polite decline / yes: work sample passed? → no: decline with feedback / yes: values interview passed? → offer.

Generate it: "Decision tree for hiring: resume screen, work sample test, values interview, each with pass/fail branches ending in offer or decline."

2. Pricing plan chooser

Need team features? → yes: more than 10 seats? → Enterprise / no: Pro. → no: exporting more than 5 files a month? → yes: Pro / no: Free.

Generate it: "Decision tree helping a customer pick Free, Pro, or Enterprise based on team features, seat count, and export volume."

3. Build vs. buy

Is this core to our product? → no: buy. → yes: does a vendor cover 80% of needs? → yes: buy and extend / no: do we have the team to maintain it? → yes: build / no: rescope.

Generate it: "Build vs buy decision tree with branches for core-to-product, vendor coverage, and maintenance capacity."

4. Refund decision

Within return window? → no: offer credit. → yes: product defective? → yes: full refund + replacement offer / no: unopened? → yes: full refund / no: partial refund.

Generate it: "Customer refund decision tree based on return window, defect status, and whether the product is opened."

Support and engineering decision tree examples

5. Support ticket triage

Service down for the customer? → yes: P1, page on-call. → no: blocking a paid workflow? → yes: P2, same-day response / no: how-to question? → yes: send docs + macro / no: P3 backlog.

Generate it: "Support triage decision tree that classifies tickets into P1, P2, P3 or docs-response based on severity questions."

Start from a similar editable template: Customer Support Flow Diagram (intake, triage, knowledge-base deflection, tier escalation).

6. Incident severity

Data loss or security impact? → yes: SEV-1. → no: majority of users affected? → yes: SEV-2 / no: workaround exists? → yes: SEV-4 / no: SEV-3.

Generate it: "Incident severity decision tree assigning SEV-1 to SEV-4 based on data impact, user scope, and workaround availability."

Start from a similar editable template: Incident Response Decision Tree (alert, severity triage, mitigation, postmortem).

7. Flaky test handling

Failure reproduces locally? → yes: fix now. → no: failed 3+ times this week? → yes: quarantine + ticket / no: re-run and log.

Generate it: "Decision tree for handling a failing CI test: reproduce locally, check flake frequency, then fix, quarantine, or re-run."

Everyday decision tree examples

8. "Should I buy it?"

Do I need it this month? → no: wait 30 days. → yes: is it under my fun-money budget? → yes: buy it / no: does it replace something broken? → yes: buy it / no: save for it.

Generate it: "Personal purchase decision tree with branches for urgency, budget fit, and replacement need."

9. Career move

Does the new role grow a skill I want? → no: stay. → yes: is total comp at least equal? → yes: take it / no: does it unlock a clearly better role in 2 years? → yes: take it / no: negotiate or stay.

Generate it: "Career decision tree weighing skill growth, compensation, and future optionality, ending in take it, negotiate, or stay."

10. Eat in or order out

Groceries in the fridge? → no: order. → yes: more than 30 minutes to cook? → no: cook / yes: is it a weeknight? → yes: order / no: cook.

Generate it: "Lighthearted dinner decision tree based on groceries, cooking time, and day of week."

How to make a decision tree

The manual way works in any tool: write the root question, add a branch per answer, and keep splitting until every path hits an outcome. The problems appear at edit time — insert one new question near the root and you're re-dragging half the tree.

The faster way is to describe the tree in plain text and let AI draw it:

1. Open the Infogiph canvas (free, no credit card).
2. Type or paste your decision logic — the prompts above are the exact format that works.
3. Generate. The AI lays out the branches, spacing, and icons automatically.
4. Edit any node, add branches, and restyle on the canvas.
5. Export as PNG or SVG — or as an animated GIF/MP4 where branches reveal in sequence, which is ideal for training decks and social posts.

Because the layout is generated, adding a question near the root is a one-line edit instead of a half-hour of realignment.

Prefer to start from a finished structure? Open the decision tree diagram template, a root decision branching to approve, review, reject and escalate outcomes, and rename the nodes to match your logic.

Frequently asked questions

What is a decision tree with an example?

A decision tree is a branching diagram that answers one question per step until it reaches an outcome. Example: a refund tree asks "within the return window?", then "is it defective?", then "is it unopened?" — and each path ends in full refund, partial refund, or store credit.

Is a decision tree the same as a flowchart?

They're close relatives. A decision tree only branches outward from a single root and never loops back, which makes it ideal for classification and judgment calls. A flowchart can loop, run steps in sequence, and return to earlier stages. If you need loops, you want a flowchart.

What is the best free decision tree maker?

Any tool that gives you editable output without payment works; the differentiator is how much manual layout it demands. Infogiph generates the tree from a text description on its free plan (5 AI generations; free exports carry a small watermark), so you skip the drag-and-drop stage entirely and just edit the result.

Can I make a decision tree in Word or PowerPoint?

Yes, with SmartArt hierarchy shapes — but every edit means manual re-alignment, and wide trees quickly outgrow the slide. Generating the tree first and pasting the exported PNG/SVG into your document is usually faster.

Copy an example and make it yours

Pick any tree above, paste its prompt into the AI flow chart maker, and you'll have an editable, animated version of it in under a minute — swap in your own questions and export wherever the decision needs to be seen.