Thickness loss due to corrosion wear generally occurs on ship structural members in corrosive environments. For corrosion wear, a probabilistic model can be successfully identified from the thickness measurements data to evaluate and estimate wear conditions. On the other hand, thickness loss due to mechanical wear may occur in some ship structural members in addition to thickness loss due to corrosion wear. In this study, a new probabilistic model for the case where mechanical wear is superimposed to corrosion wear is proposed. The condition observed in the actual structure is a mixture of corrosion wear condition and condition of corrosion wear with mechanical wear. When identifying a probabilistic model based on the plate thickness measurements data, it is impossible to distinguish whether the measurements data represent a corrosion condition due to corrosion wear or corrosion wear with mechanical wear. Therefore, a method is examined to obtain a model that would be the maximum likelihood by classifying the data using latent variables. By classifying the data and identifying both of a probability model of corrosion wear and a probability model of corrosion wear with mechanical wear, respectively, the posterior distribution of the latent variables is updated. These processes are repeated until the likelihood of the mixed probability models is maximized. For verification, a set of corrosion data consisting of mixed wear conditions were simulated and analyzed. It shows that both probability models could be properly identified with the proposed method, and in particular, the amount of diminution corresponding to high cumulative probability could also be properly estimated. Furthermore, this method was applied to thickness measurements data of ship structural members in the lower cargo holds of bulk carriers, where mechanical wear is also a concern, and it was confirmed that there was no difference in the corrosion wear condition of the members in the lower part of cargo holds of bulk carriers, however, significant differences were observed in the degree and extent of mechanical wear, indicating that the influence of mechanical damage is very significant in the wear condition of these members.