Challenging the role of expected utility theory as the defining benchmark of rationality, ample evidence shows that people violate its axioms and predictions. At least two responses to ‘choice anomalies’ have emerged. One has been to modify the theory while retaining its mathematical expectation scaffolding (e.g., cumulative prospect theory; Tversky & Kahneman, 1992). A second response has been to explain risky choice as the direct consequence of the use of boundedly rational heuristics (e.g., priority heuristic; Brandstätter, Gigerenzer, & Hertwig, 2006). These two approaches to modeling risky choice - algebraic models in the expectation family and models of heuristics - have often been featured as opposite and incompatible views of human decision-making. The goal of this project is to bridge the gap between these approaches and to demonstrate that each can benefit enormously from the other. In particular, we aim to show that the use of specific heuristics results in distinct and identifiable parametric signatures when measured in terms of the psychophysical framework assumed by algebraic models such as cumulative prospect theory. Moreover, we will show that characteristic regularities in risky decision-making as measured by cumulative prospect theory’s functions - including loss aversion, risk aversion, and insensitivity to probabilities - stem from the operation of specific heuristics.