Guide to understanding decision trees

What is a decision tree?

A decision tree is a type of flowchart you can use to visualize a decision-making process. Decision trees help you map out different courses of action and their potential outcomes. By providing an organized decision-making framework and a systematic approach to exploring all of your options, a decision tree can more easily predict your chances of a successful outcome depending on the path of action you choose.

Decision trees are similar to flowcharts in terms of layout, but they are specifically designed for decision-making, not process and workflow documentation. Decision trees are commonly used in strategic planning, research, risk analysis, and other business functions.

Decision tree symbols

Decision trees rely on many symbols to represent the different parts of the choice and the potential outcomes. Common decision tree symbols include:

Root node This top-level node contains information about the ultimate objective or main question you're exploring.
Decision node Contains information about a decision to be made; also referred to as a square leaf node.
Chance node Contains details about a chance event or uncertain outcome; also referred to as a circle leaf node.
Alternative branches These branches indicate a possible outcome, action, or event.
Rejected alternative These are branches that show a possible choice that was not selected. Rather than deleting these rejected branches, it's helpful to leave them to provide context and information about all possible choices.
Endpoint node Indicates the decision tree's conclusion; contains information about the final outcome.

Examples of when to use a decision tree

Decision trees give you a visual framework with which to organize your thoughts surrounding a decision. With this approach, you can systematically explore each available option and all potential outcomes.

Professionals in different industries and roles use decision trees to map out all types of business decisions. Some decision tree example use cases include:

Data analytics and machine learning

Decision trees are important for data analytics and machine learning—both humans and machines use decision trees to analyze and sort data. In fact, most modern algorithms are based on a type of decision tree. Engineers and computer scientists can use decision trees to design algorithms and understand how algorithms behave.

Determining viability for a new product or entering a new market for an existing product

Decision trees can be a valuable tool for entrepreneurs and business development specialists looking to launch a new product or enter a new market with an existing product. Using market data that you've collected and a series of key questions, you can create a decision tree to help you assess product viability and market opportunities.

Risk management

Decision trees are a helpful tool for risk management and strategic planning. When you create a decision tree, you end up with a robust tool for evaluating which decision paths have an acceptable level of risk and which are too volatile to pursue. Risk consultants and insurance analysts could use tree diagrams for risk analysis and management.


The decision tree's systematic framework helps finance teams consider all possible outcomes of any given financial decision, leading them to the best option for overall organizational health.

Benefits of decision trees

Benefits of decision trees

Decision trees help you make decisions by showing you every possible choice and outcome. Some key benefits of decision trees include:

Easy to follow and understand complex issues

Decision trees provide a visual framework for decision-making. Visual aids are proven to boost memory retention and make it easier to recall important details. When you have a complex issue to analyze or a weighty decision to make, using a visual tool can help streamline the process. Decision trees are easy to make and follow and can help simplify even the most complex issues.

More informed decision making

When you take the time to see all sides of an issue and explore all possible outcomes, you're more likely to make a decision that leads to a positive outcome. Decision trees are designed for exactly this purpose—forcing you to slow down and consider the decision from every possible angle.

How to make a decision tree

To create a decision tree, follow these simple steps:

  1. Start with your major decision at the root node. The root of the decision tree should reflect your main objective or decision you're trying to make.
  2. Draw your first set of arrows to indicate the different branches. Starting from the root node, draw arrows or lines for every possible option. You may want to add notes pertaining to the costs and risks associated with each course of action.
  3. Attach leaves at the end of your branches. What are the results you can expect to see from each option in the branches? Draw a square leaf node to represent another decision you have to make or draw a circular node if the result of a course of action is uncertain.
  4. Determine the probability of success of each decision. Doing adequate research is crucial when creating a decision tree, as it can help you reliably predict your chances of success. Research may include things like assessing your previous projects or studying data from your industry.
  5. Keep adding branches and leaves. Continue building onto your decision tree with more options, actions, and outcomes.
  6. Calculate risk vs. reward. Evaluate the value that you expect from each decision in the diagram. Risk vs. reward analysis will help you manage risk and maximize the odds of reaching a rewarding outcome.
  7. Make your decision. Once you've evaluated all possibilities, probabilities, and risks, decide on a final path and conclusion. In a decision tree, a triangle is used to represent the endpoint node or final outcome.

Why use MindManager to make decision trees

With decision tree software like MindManager, you can create dynamic visualizations to facilitate your decision-making activities. Features of MindManager include:

  • User-friendly, intuitive interface allows for faster onboarding and easy productivity
  • Extensive image library—over 700 topic images, icons, and symbols to add to your decision trees
  • Convenient file storage, retrieval, and sharing
  • Powerful integrations with file storage apps like Box and OneDrive
  • Google Docs integration via Zapier
  • Numerous templates, tools, and features to facilitate brainstorming and strategic planning
  • Google Chrome extension—MindManager Snap—to easily collect and import text, links, and images from the web
  • Ability to add rich data—links, images, and documents—directly to your diagrams and charts

Decision trees give you a framework for making the best choices for your team and your business. With MindManager, you gain access to a robust, digital decision tree maker with features and tools that lead to enhanced productivity, increased organization, and new and unique ways to collaborate with your team.

Decision tree templates

MindManager comes pre-installed with decision tree templates. To use these templates:

  • Open MindManager
  • Click NEW in the navigation menu
  • Select the template you want to use
  • A preview screen will appear - check to see if you'd like to use your selected template
  • Select 'Create Map'
  • Customize the template for your specific project

Decision tree FAQs

What is the difference between a flowchart and a decision tree?

Flowcharts are commonly used to describe and display the different tasks involved in a particular process or workflow. Decision trees, while similar in layout, are used to visualize a decision-making process.

What are the components of a decision tree?

The main components of a decision tree include a root node, decision nodes, chance nodes, alternative branches, and an endpoint node. Optional features include rejected alternatives.

Go out on a limb — make a decision tree

Rather than relying on your intuition or a gut feeling for your next big decision, try creating a decision tree. With a decision tree, you'll have a helpful visual framework for organizing ideas and data related to your decision. Decision trees help you systematically explore all available possibilities to reach the best outcome. They're easy to follow and lead to more informed decisions backed by research and data.

Visualize more with MindManager

MindManager enables you to intuitively gather, connect, and analyze the data relating to important business decisions. With user-friendly, premade templates, you can quickly organize your information and get one step closer to making your next key decision. To create your own decision tree try MindManager for free today.

Try the full version of MindManager FREE for 30 days