This chapter reviews models of choice on two levels: The first concerns the descriptions of choice and their evolution from normative models of how choices should be make to more behaviorally realistic models, more consistent with data showing that choice depends heavily on context. We present brief overviews of risky and riskless choice models and data and for choice over time. We then turn to computational process models, a more recent class of models that make prediction for multiple properties of the decision process beyond simply what is chosen, including predicting the distribution of errors and decision times.These models are typically applied to simpler choices, but have found great use in contemporary neuroscience.