In this chapter we give an overview of Bayesian statistics and specifically we consider Bayesian inference methods which are used in data fusion. We first briefly consider the methods of conjugate and non-informative distributions. We then consider in detail the Gaussian Mixture model and the method of expectation-maximization including the problem of missing data. Finally we consider the problem of model selection including Bayes information criterion.