This chapter provides the goal of building person– context systems of health behavior, with equal attention to both the person and context. It reviews the nascent field: the computational health behavior modeling approach, a subfield of health behavior that emphasizes the use of computational and mathematical modeling for representing health behavior theory. These criteria define the desired qualities of a useful health behavior theory that can promote the unification of social networks and health behavior to scale. The field of computational health behavior modeling, to date, has only used two formalisms: dynamical systems and artificial neural networks. The dynamical systems approach, led by Daniel Rivera at Arizona State University, provides a control systems engineering perspective on health behavior. The neural networks approach to modeling health behavior was highly influenced by work in social cognition, an area of research that encapsulated the first sketch of the potential promise of computational modeling of health behavior.