Statistically significant quantitative structure-toxicity relationship (QSTR) models have been developed for assessing developmental toxicity potential (DTP) of chemicals. Three submodels, one each for aliphatic, heteroaromatic and carboaromatic compounds, have been cross-validated to ascertain their robustness. The specificities of the models range from 86% to 97%, and their sensitivities between 86% and 89%. For convenient computer-assisted application, the models are installed in a toxicity assessment software package, TOPKAT, which has been recently enhanced with algorithms to identify whether or not a query structure is inside the optimum prediction space (OPS) of a QSTR model. Different functionalities of the TOPKAT program have been explained by assessing the DTP of a number of compounds not used in the model training sets. The DTP of 18 existing drugs was assessed using these models; the DT assay results were available for 5 of these. Three of these 5 molecules were identified to be inside the OPS and their TOPKAT assessment matched their experimental assignment.