Information theory, when combined with incoherent system modelling, can be a powerful design tool. Specifically, the Cramer-Rao bound can be used to predict the performance of a given modelled system. The Cramer-Rao bound is a lower bound on estimation variance of the best estimator of an unknown parameter in the presence of unknown ``nuisance'' parameters. By minimizing the Cramer-Rao bound relative to a given modelled system the optimum system design can be found. The optimum system is one where the estimation variance of the unknown parameter is minimum over all similar systems. The Cramer-Rao bound was derived for the three example systems of single-image, single-lens, passive range estimation, range-invariant imaging, and single-image, orthogonal passive range detection systems.