Decision tree-based algorithms are used to classify data in predictive modeling. These algorithms are commonly used for constructing classifiers. The main goal of this chapter is to provide an overview of decision tree-based algorithms. Key methods discussed include boosting, attribute selection, entropy, and information gain. The chapter also covers the importance of pruning in decision tree construction.