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QSPR modelling is one of the major computational tools used to correlate molecular characteristics with physiochemical properties of molecules. In present work, QSPR models are formed using AIC and VIF multicollinearity indicators for descriptors selection taking solubility data of Paclitaxel prodrugs. Our approach can be applicable to different datasets and it can assist the synthesis of molecule with better solubility. These QSPR models can be implemented for predicting the aqueous solubility of unknown Paclitaxel prodrugs.