The most used model for predicting wear is the linear wear law proposed by Archard. A common generalization of Archard’s wear law is based on the assumption that the wear rate at any point on the contact surface is proportional to the local contact pressure and the relative sliding velocity. This work focuses on a stochastic modeling of the wear process to take into account the experimental uncertainties in the identification process of the contact-state dependent wear coefficient. The description of the dispersion of the wear coefficient is described by a probability density function, which is performed using the maximum entropy principle using only the information available. Closed-form results for the probability density function of the wear depth for several situations that commonly occur in practice are provided.