We have carried out partially unified multiple property recursive partitioning (PUMP-RP) analyses on a database of cyclooxygenase (COX) inhibitors, using CART methods implemented in Cerius2. Three sets of physicochemical descriptors (ISIS public keys, DAYLIGHT Fingerprints, and Cerius2) were computed for the database molecules which were divided into two groups, assigned as training (89%) and test (11%selected using diversity analyses tools in Cerius2) sets. The descriptors which led to the discrimination of active and selective COX-2 inhibitors included ISIS Key #59 (Snot%A%A), Balaban electrotopological index JY, partition coefficient AlogP, and Jurs surface area descriptors (FNSA, FPSA, and PPSA). A strong correlation is obtained between the predicted and experimental COX-2 inhibitory activity and a moderate correlation for selectivity of the COX-2 inhibitors, both in the training and test sets. Application of the RP trees to a validation set of Merck cyclooxygenase inhibitors shows good consistency with the COX-1 and COX-2 activity data, albeit moderate consistency with the selectivity data. Compared to the independent RP models (obtained by considering each activity separately), the PUMP-RP decision trees provide easier identification and interpretation of those descriptors that are common to both COX-1 and COX-2 activities. Similarly, they are easier to distinguish the descriptors that discriminate the two activities. The study represents a preliminary validation of the PUMP-RP method described in the previous article of this issue.