Credibility theory has provided with a useful tool the assignment of weighting factor that reflects the credibility of the observed individual and collective experience to secure fair experience rate-,making. We review credibility models which can effectively estimate risk premiums using credibility theory, and suggest an empirical Bayed model based on the collective statistics to estimate the structural parameters. To illustrate the use of evolutionary models, the models are applied to the actual data, such as loss ratio, claim frequencies and severity, in the Korean automobile insurance. Also the possibilities of generalizations and applications of empirical models are discussed.