Abstract: This study considers use of Bayesian methodology for the population projection of an Indian Province, Kerala using logistic growth model. The study presents probabilistic projections of the population and estimates of the parameters of the model along with their highest posterior density intervals. Getting actual expressions of posterior distributions in Bayesian setup with large number of parameters is a difficult task. To overcome the problem, Markov Chain Monte Carlo (MCMC) technique has been used for getting samples from the posterior distribution. The projections have been compared with those made in earlier studies to check the suitability of the projections. We have also discussed the asymptotic behavior of population projection to know the total population at which Kerala population will be stabilized.