This chapter introduces Classification and Regression Trees (CART) as powerful tools for prediction. It presents the CART algorithm, the greedy nature of the algorithm, and how it can be used for both classification and regression tasks. The chapter also discusses Random Forests as an extension of CART, that leads to increased predictive accuracy by aggregating multiple decision trees. Examples in R illustrate the application of CART and Random Forests to real estate data, demonstrating their practical use in predictive modeling.