Polychlorinated dibenzo-p-dioxins(PCDDs) are a group of important persistent organic pollutants.They are highly toxic and persistent in environment.In the present study,geometrical optimization and electrostatic potential calculations have been performed for 75 PCDD congeners and dibenzo-p-dioxin(DD) at the HF/6-31G* level of theory.A number of statistically based parameters have been extracted.Linear relationships between vapor pressures(logpL),aqueous solubilities(logSw),n-octanol/water partition coefficients(logKow) of PCDDs and structural descriptors have been established by stepwise linear regression analysis.The result shows that the quantities derived from the surface electrostatic potentials Vmin,Π,and Vs,av+,together with Vmc(the molecular volume) and ELUMO(the energy of the lowest unoccupied molecular orbital) can be well used to express the quantitative structure-property relationships of PCDDs.Predictive capabilities of the models have also been demonstrated by leave-one-out cross-validation with the cross-validated correlation coefficient(Rcv) above 0.97.Based on these QSPR models,the predicted values have been presented for those PCDD congeners whose experimentally determined physicochemical properties are unavailable. Polychlorinated dibenzo-p-dioxins (PCDDs) are a group of important persistent organic pollutants. They are highly toxic and persistent in the environment. The present study, geometrical optimization and electrostatic potential calculations have been performed for 75 PCDD congeners and dibenzo-p- dioxin (DD) at the HF / 6-31G * level of theory. A number of statistically based parameters have been extracted. Line relationships between vapor pressures (logpL), aqueous solubilities (logSw), n-octanol / water partition coefficients ) of PCDDs and structural descriptors have been established by stepwise linear regression analysis. The resulting shows that the quantities derived from the surface electrostatic potentials Vmin, Π, and Vs, av +, together with Vmc (the molecular volume) and ELUMO (the energy of the lowest unoccupied molecular orbital) can be well used to express the quantitative structure-property relationships of PCDDs.Predictive capabilities of the models have also been demonstrated by leave-one-o ut cross-validation with the cross-validated correlation coefficient (Rcv). 0.97. Based on these QSPR models, the predicted values ​​have been presented for those PCDD congeners whose experimentally determined physicochemical properties are unavailable.