Mass spectrometric data can be obtained for compounds in bead-bound combinatorial mixtures by several techniques. However, little specific information is available regarding (1) how well these data differentiate between candidate structures in large combinatorial pools, (2) what precision of data is required to achieve adequate specificity in these analyses, and (3) what are the best strategies for applying these data. In this work, computer modeling is used to address these questions. Strategies employing multiple filters (i.e., those that differentiate possible structures using more that one measured mass spectral parameter) are found to provide better specificity and to be more robust (that is, the specificity is less dependent on the precision of the data) than discrete filters. With moderate precision data (e.g., 50 ppm mass precision, 10% isotope ratio precision), multiple filter strategies are found to give unequivocal results for ∼80% of the populations of combinatorial mixtures with most of the remaining degeneracy at the 2-fold level. A simple protocol for the application of multiple filter methods is presented.