A comprehensive rigorous theory is developed for screening sensitivity coefficients in large-scale modeling applications. The theory uses Bayesian inference and group theory to establish a probabilistic framework for solving an underdetermined system of linear equations. The underdetermined problem is directly related to statistical screening sensitivity theory as developed in recent years. Several examples of the new approach to screening are worked out in detail and comparisons are made with statistical approaches to the problem. The drawbacks of these latter methods are discussed at some length.