Zusammenfassung: The Bayes posterior probability distribution is a powerful way to represent uncertainty in fisheries stock assessments, and can be calculated for key population and policy parameters of practically any population dynamics model. But the calculation is unwieldy when probabilities are to be assigned to a large grid of parameter combinations. The computational burden can be reduced substantially by analytically integrating over at least two “nuisance parameters” that occur in most assessment models: the observation error variance and the catchability coefficient. This simplification allows the analyst and manager to focus more easily on population parameters (stock size, slope of recruitment curve) that are of direct policy interest.