Bayesian inference, incorporating prior information, will be quite useful in developing inference for one-shot device testing data, especially in the case of small sample sizes. This chapter describes the Bayesian inferential method for one-shot device testing data under constant-stress accelerated life-tests (CSALTs), as originally developed by Fan et al. Under the Bayesian framework, it begins with the conditional joint likelihood function. In Bayesian inference, the prior information plays a very important role, especially when the data provide insufficient information about the parameters. Some commonly used priors and the corresponding hyperparameters, based on experts’ information, are detailed. Extensive simulation studies are performed to evaluate the performance of the proposed Bayesian estimation methods for one-shot devices under CSALTs. The chapter considers the R codes for defining the glass capacitors data under CSALTs.