This chapter presents advanced and emerging topics in predictive process monitoring. The first topic concerns neuro-symbolic techniques, that is, the integration of neural networks with symbolic systems applied to this field. Next, explainable artificial intelligence techniques are introduced to provide users with understandable explanations for the predictions made by a model on ongoing process instances. Multimodal predictive process monitoring is then discussed, which considers multiple data modalities (such as images, video, audio, and control flow) during the learning phase of a process execution. The chapter concludes with prescriptive process monitoring, focusing on techniques that provide users with actionable recommendations which, if followed, can lead to positive outcomes for ongoing trace executions.