Despite its rapid growth across several social science disciplines, the use of the Bayesian approach to measure tourism performance has yet to gain strong attention in tourism research. This article reviews the foundation of the Bayesian approach and discusses its benefits and the flexibility it provides in the estimation of highly complicated performance models. With the lack of tourism studies focusing on the Bayesian approach, we take first a general approach and provide a description of the Bayesian approach, illustrating its advantages, and its key differences from the frequentist approach. We then discuss its specific benefits in the measurement of tourism performance within the context of stochastic frontier (SF) models. We introduce several advanced versions of SF where the use of the Bayesian approach becomes necessary. We also provide simulation evidence about the advantages of the Bayesian approach and discuss how it can be used to estimate various SF models.