The Large-Scale Structure of Inductive Inference investigates the relations of inductive support on the large scale, among the totality of facts comprising a science or science in general. These relations form a massively entangled, non-hierarchical structure which is discovered by provisional hypotheses that are later supported by other facts drawn from the entirety of the science. What results is a benignly circular, self-supporting inductive structure in which universal rules are not employed, the classical Humean problem cannot be formulated and analogous regress arguments fail. Building upon and furthering The Material Theory of Induction, this book presents general claims and arguments for the large-scale relations of inductive support according to the material theory of induction, in which inductive inferences are not warranted by universal rules but by facts particular to each context. It begins with a thorough discussion of general claims and arguments for the large-scale structure of inductive relations, followed by case studies in the history of science that support, and further illustrate, those claims. With The Large-Scale Structure of Inductive Inference, author John D. Norton presents a novel, thoroughly researched, and sustained remedy to the enduring failures of formal approaches of inductive inference.