Previously, we utilized high throughput screening of a chemical diversity library to identify potent inhibitors of human neutrophil elastase and found that many of these compounds had N-benzoylpyrazole core structures. We also found individual ring substituents had significant impact on elastase inhibitory activity and compound stability. In the present study, we utilized computational structure-activity relationship (SAR) analysis of a series of 53 N-benzoylpyrazole derivatives to further optimize these lead molecules. We present an improved approach to SAR methodology based on atom pair descriptors in combination with 2-dimensional (2D) molecular descriptors. This approach utilizes the rich representation of chemical structure and leads to SAR analysis that is both accurate and intuitively easy to understand. A sequence of ANOVA, linear discriminant, and binary classification tree analyses of the molecular descriptors led to the derivation of SAR rule-based algorithms. These rules revealed that the main factors influencing elastase inhibitory activity of N-benzoylpyrazole molecules were the presence of methyl groups in the pyrazole moiety and ortho-substituents in the benzoyl radical. Furthermore, our data showed that physicochemical characteristics (energy of frontier molecular orbitals, molar refraction, lipophilicity) were not necessary for achieving good SAR, as comparable quality of SAR classification was obtained with atom pairs and 2D descriptors only. This simplified SAR approach may be useful to qualitative SAR recognition problems in a variety of data sets.