Probability Tree Diagram Maker

A probability tree diagram is a branching chart that maps out all possible outcomes of a sequence of events, with each branch labeled with its probability. It helps you visualize how combined probabilities flow from one decision or chance event to the next. They are widely used in statistics, business, and risk analysis.

You can either describe your scenario in plain language and let the AI build the tree, or construct it manually using the node editor. Add decision nodes, chance nodes, and outcome nodes, then label each branch with conditions and probabilities. The layout renders instantly as you build.

Yes. MakeCharts lets you create and export probability tree diagrams for free with no sign-up required. Free accounts also include limited AI credits to try AI-generated diagrams. Paid plans unlock more AI credits, file upload, and advanced export options.

A decision tree includes decision nodes (choices you control), chance nodes (events with probabilities), and outcome nodes (results). A probability tree diagram is a subset that focuses specifically on mapping probabilities across branching events. This tool supports both structures using distinct node types.

Yes. Type a plain-language scenario — like 'a medical test with 90% sensitivity and 85% specificity applied to a population with 5% disease prevalence' — and the AI will generate the full probability tree with labeled branches and probability values ready to edit.

In the node editor, each branch (edge) has a probability field where you can enter a value between 0 and 1. Enable 'Show Probabilities' in the Display settings to render all probability labels on the exported diagram. Edge labels can also show condition names alongside the numeric probabilities.

Yes. You can download your probability tree diagram as a high-resolution PNG or vector SVG file. PNG is ideal for presentations and documents, while SVG scales to any size without losing quality — useful for embedding in websites or printing.

Absolutely. Bayes theorem problems are a classic probability tree use case. You can model prior probabilities, conditional branch probabilities, and trace paths to calculate posterior probabilities. The visual layout makes it easy to identify each path and multiply probabilities correctly.

Yes. You can switch between a left-to-right layout (ideal for wide slides) and a top-to-bottom layout (ideal for deep trees or printed documents) in the Layout settings panel. Node spacing is also fully adjustable.

Yes. Teachers can generate example probability trees instantly to illustrate compound events, independent vs. dependent events, and expected value calculations. Students can build their own diagrams for assignments and export them as images to submit or present.