The network approach to clinical psychology is a relatively new approach and diverges on various aspects from existing models and theories. The hallmark of the theory is that there is no common cause that underlies a set of symptoms. Instead, the network approach starts out by assuming that symptoms causally interact with each other. In this chapter, we first explain the conceptualization of psychological phenomena as a network in the introduction. Second, we provide an overview of the methods that are used to construct network models from data; both Gaussian and binary data, as well as cross‐sectional and longitudinal data are covered. Third, we describe how a given network can be analyzed to uncover important symptoms in the network, to predict behavior of the network, and to compare network structures. Fourth, we discuss current state‐of‐the‐art research in clinical psychology and psychiatry, to see what these networks taught us about psychopathology. Finally, we discuss the promising prospects for clinical psychology research that the network approach has to offer and some of the challenges a researcher might face in applying this approach to clinical psychology data.