Process mining offers a rich tool set for analyzing event data which record information about events that occur during the execution of processes. Event attributes captured in those data include, at a minimum, the type of executed activities, the temporal ordering of events, and the process instance to which an event belongs, but can also cover additional aspects like the involved resource or the execution status of activities. Given the distributed, temporal, and concurrent nature of blockchain technology, process mining is a valuable addition to the blockchain analytics tool set, allowing applications to be analyzed through a process lens. In this chapter, we summarize the current state of the art regarding process mining for blockchain analytics. Starting from a process mining methodology for blockchain analytics, we provide an overview of available techniques and tools for the two most important analysis steps: data extraction and preparation as well as data analysis and visualization. We then discuss promising use cases and limitations of process mining for blockchain analytics and present an illustrative real-world case study involving a DApp deployed on the public Ethereum network.