The predictive processing framework (PPF) attempts to tackle deep philosophical problems, including how the brain generates consciousness, how our bodies influence cognition, and how cognition alters perception. As such, it provides a zeitgeist that incorporates concepts from physics, computer science, mathematics, artificial intelligence, economics, psychology, and neuroscience, leveraging and, in turn, influencing recent advances in reinforcement learning and deep learning that underpin the artificial intelligence in many of the applications with which we interact daily. PPF purports to provide no less than a grand unifying theory of mind and brain function, underwriting an account of perception, cognition, and action and their dynamic relationships. While mindful of legitimate criticisms of the framework, to which we return below, an important test of PPF is its utility in accounting for individual differences such as psychopathology. These, then, are the central concern of this special section of the Journal of Abnormal Psychology: What is the state of the art with regards to applying the PPF to the symptoms of mental illness? How might we leverage its insights to elevate and systematize our explanations, and ideally treatments, of those symptoms? And, conversely, can we refine and refute aspects of the PPF by considering the particular challenges that our patients experience as departures from the parametric estimates of the PPF? (PsycInfo Database Record (c) 2020 APA, all rights reserved).