Mathematical-programming formulations can yield faulty answers. Models can be unbounded, infeasible, or optimal with unrealistic answers. I develop techniques for screening mathematical-programming formulations for structural problems pre- and postsolution. The presolution approaches identify problems within single variables and constraints. The postsolution techniques may require model augmentation and rely on theory-based examination of primal and dual solutions. I demonstrate these approaches in the context of linear programming and have computerized them in association with GAMS. They are freely distributed through a web page.