We present an algorithm to approximate the solutions to variationalproblems where set of admissible functions consists of convex functions. The mainmotivation behind the numerical method is to compute solutions to Adverse Selectionproblems within a Principal-Agent framework. Problems such as product lines design,optimal taxation, structured derivatives design, etc. can be studied through the scopeof these models. We develop a method to estimate their optimal pricing schedules.