This chapter is central to the book, as it introduces the main predictive techniques for addressing predictive process monitoring tasks. It begins with an overview of approaches that leverage an explicit process model to make predictions (process model-based approaches). The chapter then explains how machine learning methods can be used to build predictive models that provide forecasts about ongoing trace executions. Finally, classical machine learning techniques are presented first, followed by modern deep learning approaches.