In this work, an effort has been made to obtain a QSPR skin sensitization model with wide applicability. An extensive database comprised of test results from three exclusive test procedures were used for the QSPR model development. This work focuses primarily on the following objectives: (a) Develop QSPR models to predict skin sensitization. Since the experimental procedure and end point ranking for local lymph node assay (LLNA), guinea pig maximization test (GPMT) and Federal Institute for Health Protection of Consumers and Veterinary Medicine (BgVV) are different, three exclusive QSPR models were developed, and (b) Improve the predictive capability of the QSPR models using a combination of literature recommended and statistically determined descriptors. The resultant QSPR models are capable of predicting critical properties of the diverse set of molecules considered with an accuracy of 88%, 93% and 90% for LLNA, GPMT and BgVV datasets, respectively.