In this paper we propose an experimental method to choose a prior distribution. Different from many re-searchers, who offered lots of principles that separated from sample information, we consider it a Bayesian discrimina-tion problem combining with the sample information. We introduce the concept of Posterior belief about prior distri-butions. With the well-known Bayes theorem we give out a formula to calculate it and propose a method to discrirni-nate a prior between prior distributions-- Highest Posterior Belief (HPB). We also show that under certain condition,the HPB method is identical with the ML-I method.
