A quantitative structure–property relationship (QSPR) study was performed to develop models those relate the structures of 32 Kovats retention index (RI) of AD.Molecular descriptors derived solely from 3D structures of the molecular compounds. A genetic algorithm was also applied as a variable selection tool in QSPR analysis. The models were constructed using 25 molecules as training set, and predictive ability tested using 7 compounds. Modeling of RI of ADD as a function of the theoretically derived descriptors was established by multiple linear regression (MLR). The usefulness of the quantum chemical descriptors, calculated at the level of the HF theories using 6-31+G** basis set for QSAR study of AD was examined. The use of descriptors calculated only from molecular structure eliminates the need for experimental determination of properties for use in the correlation and allows for the estimation of RI for molecules not yet synthesized. Application of the developed model to testing set of 7 drug organic compounds demonstrates that the model is reliable with goo predictive accuracy and simple formulation. The prediction results are in good agreement with the experimental value. A multi-parametric equation containing maximum Four descriptors at B3LYP/6-31+G** method with good statistical qualities (R2 train=0.922, Ftrain=109.04, R2 test=0.848, Ftest=4.35, Q2 LOO=0.904, R2 adj=0.914,Q2 LGO=0.862) was obtained by Multiple Linear Regression using stepwise method.