Climate change is often framed as a scientific truth beyond doubt. Such a framing responds to exploitation of doubt by climate sceptics, while it also suits the logics of dominant approaches to climate governance. Yet the possibility of harm from climate change often resides at epistemic loci where prediction becomes more speculative or finds its limits. This book explores how digital climate models and associated climate technologies negotiate uncertainty imposed by climate change. It addresses how computational models, which often use numerous datasets and AI, produce knowledge at the limits of computability and predictability. Furthermore, this book presents a series of case studies in support of theory development revolving around mediated experiences of users such as investors, farmers, and urban consumers, situated across the global north and south. By considering the social consequences of model prediction and computation as well as of their limits, this book shows climate injustice through a new lens, informed by digital media studies and science and technology studies (STS).