The effects of regulations on recreational fishers are especially difficult to predict. Data lags typically prevent in-season management, so regulations restrict aspects of individual fishing activity in the hopes of achieving collective catch limits. This study began with discrete choice surveys to elicit angler preferences among various types of fishing trips (including none at all). Trip choices varied in the species composition, number, and size of fish caught, as well as how many could be retained. The results of these surveys allowed us to provide a statistical representation of angler preferences. These preferences were then incorporated into models of fishing behavior in which catch probabilities were modeled using data from actual fishing trips, but potentially constrained by regulation. The model included additional dynamics for selected species by making the probability of catches vary with stock abundance, which in turn varied across years of a model run based on overall fishing pressure. The goal of this angler regulation assessment tool include (a) research to improve our understanding of fishing behavior and (b) operational use to guide managers in setting recreational bag, size, and seasonal limits suitable to achieve recreational catch allocations.