This paper is concerned with the performance evaluation of multiple-target tracking systems, in particular, with evaluating the quality of tracks as the outputs of such systems. Very simple analytic functions are developed to relate key tracking environment parameters to a selected tracking performance measure, i.e., track purity, which is an important quantification of the tracking output quality when single-frame based target classification is not possible. The method for predicting track purity is based on a simple mathematical model for data correlation performance within a single data set. Several Monte Carlo simulations are performed to verify the applicability of the analytic functions.