<p>Transmuted distributions have been centered of focus for the past few years for their flexibility and the ability to better fit the real life phenomena. Inspired by the feature of the transmuted family of distributions, one of its subclasses, the Transmuted Rayleigh distribution (TRD) has been considered for Bayesian analysis in this article to further explore significant aspect of this class. The mathematical expressions of Bayesian Estimators (BEs), Bayes Risks (BRs) and Bayesian credible intervals (BCIs) are evaluated using type-I censoring scheme. The Uniform prior (UP) as non-Informative prior (NIP) and Gamma prior (GP) as Informative prior (IP) for the model parameter, have been assumed for posterior Bayes analysis. To develop Bayesian estimation methodology, three different loss functions (LFs), namely, logarithmic loss function (LLF), precautionary loss function (PLF), and weighted balance loss function (WBLF) are employed. Extensive MCMC simulation analysis under different scenarios has been carried out. The anxiety data from a study on healthy women has been taken into consideration to demonstrate the applicability of this methodology. After careful observation in simulation study and real data set, IP produce more efficient results. Additionally, PLF performs better when dealing with transmuted parameter, while WBLF shows better performance when dealing with scale parameter.</p>