In this note we propose an application of the method of maximum entropy in the mean to solve a class of inverse problems comprising classification problems and feasibility problems appearing in optimization. Such problems may be thought of as linear inverse problems with convex constraints imposed on the solution as well as on the data. The method of maximum entropy in the mean proves to be a very useful tool to deal with this type of problems.