In order to provide insulators with scientific guide for the prevention of contamination flashover， the key is to optimize the input of the forecast model and to increase the time margin of pre-warning. The leakage currents（LCs） of insulators with different pollution levels are measured in the same period after the pollution layers are saturated moist in the fog chamber. Three characteristics based on the effective value of LCs and the fitting equations of three characteristics and pollution levels are established. In addition， the relation between the three characteristics and pollution levels are compared for two kinds of insulators with different leakage distances， namely， the general suspension insulator（GSI） and the anti-pollution suspension insulator（ASI）. The reason the three characteristics of ASI are less than those of GSI is deduced. Furthermore， the neural network model with the input of the three characteristics of LC is put forward at the safe stage of LC to forecast the pollution levels of insulators. The error with this model is less than 4%. Finally the influence of the three characteristics on the forecast results is analyzed. The research findings have provided not only a theoretical basis for the characteristic selection of the pre-warning system of transmission lines， but also the decision on clearing polluted insulators.