Bayesian statistics allows one to use prior information with the data through Bayes theorem which provides the formal basis for making use of both sources of information in a formal setting. In some sense, Bayesian analysis can be considered as the study of different features arising out of the posterior distribution. Due to its direct relevance and potential utility in clinical research, Bayesian statistics is increasingly becoming more popular in medical literature. The statistical methodology underpinning this technique and software tools, both commercial and open source, for implementing the methods continue to evolve with some newer tools being more general while some are analysis-specific. The Bayesian community has contributed to this growth by developing numerous software tools specific to Bayesian analysis. These software tools come with varying degrees of functionality, complexity, and ease of use. This chapter aims to provide a brief introductory overview to some selected software tools for Bayesian analysis. Both commercial and open source tools will be discussed. To help elucidate the functionality of the software tools considered, we will describe each software with regards to its functionality and provide some illustration in some instances of usage via some applications as well as provide graphical viewpoint along with some recommendations where appropriate.