This chapter focuses on the encoding of trace prefixes into an appropriate format that enables existing machine learning algorithms to train predictive models. Encoding plays a crucial role in predictive process monitoring, as it determines how information contained in event logs is represented and subsequently interpreted by learning algorithms. The chapter presents three main families of encodings—sequential, process-aware, and graph-based—that are commonly used in this domain, providing some of their representative instantiations.