The article introduces a method for choosing the best prior distribution in Bayesian analysis. By using the theory of posterior distribution, the researchers developed a way to calculate the posterior distribution of the prior. This allows for the selection of a reasonable prior based on the posterior distribution, leading to the creation of a new Bayesian Prior selection method. This method is an extension of a previous approach called ML-Ⅱ prior.