Chloronaphthalenes (PCNs,polychlorinated naphthalenes) are a group of persistent environmental pollutants. In the present study,geometrical optimization and electrostatic potential calculations have been performed for all 75 PCNs at the HF/6-31G* level of theory. A number of statistic based parameters have been extracted. Linear relationships between gas-chromatographic retention index (RI) of 62 PCNs in a non-polar column (DB-5) and the structural descriptors have been established by stepwise multiple regression technique. The result shows that two quantities derived from electrostatic potential on molecular surface,∑V_s~- and σ_+~2,together with the number of chlorine (N_(cl)) and the energy of the highest occupied molecular orbital (E_(nouo)) can be well used to express the quantitative structure-retention relationship (QSRR) of PCNs. Predictive capability of the model has been demonstrated by leave-one-out cross-validation with the cross-validated correlation coefficient (R_(cv)~2) of 0.997,and further compared with the results from similar researches published recently. Furthermore,when splitting the 62 PCNs into training and validation sets in the ratio of 2:1,a similar treatment yields an equation of almost equal statistical quality and very similar regression coefficients,validating the robustness and prediction capability of our model. The QSRR model established may provide a new powerful method for predicting chromatographic properties of polychlorinated naphthalenes.