The behavioral framework is also one of the important theoretical frameworks for machine learning, especially the learning from the environment. In this chapter, we first overview behaviorism doctrine and behavioral psychology. Next, we introduce behavioral learning theory, including respondent conditioning and operant conditioning, and the later propose the concept of reinforcement learning. We then introduce behavioral decision theory and the behavior decision process and expected utility. After that, we explain two types of decision models: Bayesian decision models and Markov decision models. Finally, we present three types of behavior decisions, including single-stage decision, multistage decision, as well as sequential decision, where the sequential decision is made during the interactive learning with the environment.