Many of the world's harvested fish stocks are managed with the use of results from fish stock assessments. The penultimate goal of fish stock assessment is to evaluate the potential consequences of alternative management options. The bulk of the analytical effort is typically focused on formulating credible models of fish population dynamics, compiling data and fitting the models to data to estimate model parameters and management quantities of interest. Trends in fish stock abundance and fishing mortality rates are evaluated and the models are projected to evaluate the potential consequences of different management options. Since the mid-1990s applications of the Bayesian statistical approach to fish stock assessment have been increasing and in recent years applications have become commonplace. Debates about whether the Bayesian is appropriate for fisheries stock assessment have moved on to debates over how the approach should be applied. In this talk I review recent developments of the Bayesian approach in Canadian fisheries stock assessment with a focus on some of my recent applications to rockfish stocks that have been designated as threatened and endangered. I will highlight some of the chief merits of the approach but also problems commonly experienced with its application.