This dissertation combines three contributions to the literature on bounded rationality in games. The aim of this thesis is to improve our understanding of how individuals make decisions in games, improve our ability to model this behavior and increase our understanding of how bounded rationality affects predictions, policy and optimal mechanisms. The first paper is an application of a boundedly rational model to explain behavior in coordinated attack games. I demonstrate that the main experimental results, such as threshold strategies, comparative statics, and the differences in behavior under public and private information, are robust predictions of limited depth of reasoning models. This is in contrast to equilibrium, which mispredicts the coordinating roles of the different types of information. The analysis has implications for macroeconomic phenomena, like currency attacks and debt crises, which are commonly modeled using incomplete information coordinated attack games. The second paper explores policy and optimal mechanism design under bounded rationality. Level-k implementation is contrasted with the more standard Bayesian implementation concept. I show that the revelation principle holds with an augmented message space and that level-k implementation is a weaker solution concept. In addition, level-k implementation is possible in a mechanism that is robust to different specifications of beliefs about depths of reasoning or to any specification of beliefs about payoffs. The third paper takes a step back from assuming a particular solution concept and investigates empirical features of strategic reasoning in the lab. I employ strategic choice data from a carefully chosen set of ring games to obtain individual-level estimates of the following three epistemic conditions: rationality, beliefs about the rationality of others, and consistent beliefs. I find that not a single subject satisfies all three of the epistemic conditions sufficient for Nash equilibrium and that consistent beliefs, rather than rationality, is the more likely source for the failure of Nash equilibrium. The design allows us to weight the relative plausibility of alternative solution concepts used to explain laboratory results.