This chapter considers reasons why clinical psychologists should be interested in explaining how and why their treatments work and neural network models (NNMs) that accurately simulate both normal and abnormal behaviors, and answers the central question of what implications NNMs have for clinicians. The neural network approach to learning and memory is the only contemporary approach that is fully consilient with neuroscience because it uses brain-like mechanisms. The chapter discusses the neural network properties that constitute psychological principles that compel psychological phenomena to occur. Every psychological state entails a cascade of network activations across some neural architecture. Parallel distributed processing (PDP)-connectionist neural network (CNN) models are unique in psychology because they specify a network architecture and compute effects based on the mechanics of the network cascade. The way artificial neural networks are trained and retrained informs people about how to train and retrain biological neural networks and thereby treat a variety of psychological disorders.