The present Quantitative Structure -Activity Relationships (QSAR) study attempts to explore the structural and physicochemical requirements of O-[2-(phthalimido)ethyl]-substituted-phenylthiocarbamates for cytoprotection data from MT-4-based assays using a Linear Free Energy Related (LFER) model of Hansch. QSAR models have been developed using electronic (Hammett s), hydrophobicity (p) and steric (molar refractivity and STERIMOL L, B 1 , and B 5 ) parameters of phenyl ring substituents of the compounds along with appropriate dummy variables. Statistical techniques like stepwise regression, Multiple Linear Regression (MLR) with Factor Analysis (FA) as the data preprocessing step (FA-MLR), Partial Least Squares (PLS), Principal Component Regression (PCR), Multiple Linear Regression with Genetic Function Approximation (GFA-MLR) and Genetic Partial Least Squares (G/PLS) model were applied to identify the structural and physicochemical requirements for the cytoprotection activity. The generated equations were statistically validated using leave-one-out technique. The quality of equations obtained from these techniques were of acceptable statistical qualities (explained variance ranging from 57.7 to 75.9%, while predicted variance ranging from 53.2 to 68.5%), while the best model came from the PLS technique. The PLS equation with variables selected based on standardized regression coefficients show explained and predicted variances of 75.9 and 68.1%, respectively, and the G/PLS explained and predicted variances of 75.1 and 68.5%, respectively, of the cytoprotection activity data. Both stepwise regression and GFA derived models show high intercorrelation among predictor variables used in the equations, while the FA-MLR derived model has comparatively lower statistical quality. The best models were also subjected to leave-25%-out crossvalidation. The results of the present QSAR study are in agreement with the observations of the previously reported docking experiment of thiocarbamate derivatives.