Classification and forecasting are two recurrent words in business world nowadays. Classification aims at predicting the future class while forecasting aims at predicting the future value of a system that is intrinsically uncertain. This chapter briefly presents the main methods, focusing on the decision tree (DT) methodology. A DT is a hierarchical collection of rules that describe how to divide a large collection of units into successively smaller groups of units. In the Recursive Partitioning Steps a choice of the criteria to split the nodes is given. The prediction value of the leaf depends on the target variable Y. In fact, if Y is a numeric variable, then the prediction value of the leaf is the average mean of the variable Y. Regression trees are DTs where the target variable Y is a numerical variable. The chapter presents a binary recursive partitioning process.