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In order to improve the reliability of power transmission lines, one of the key issues is to reduce the hazard of contamination flashovers. Presently, the most efficient way is to clean (or replace) the heavily polluted insulators. The leakage current is the critical online quantity that can be detected. A number of laboratory experiments on 35 kV voltage class ceramic and glass insulators show that the leakage current fully reflects the entire process of contamination flashover development. The test results reveal that the process can be classified into three stages, i.e., security stage, forecast stage and danger stage. The results, that were duplicated several times, are based on three characteristics of the leakage current, i.e., the root-mean-square value, waveforms, and power spectrum estimation. In addition, the boundaries of the three stages in both time domain and power spectrum domain are also determined. All these can be used for the stage pre-warning of contamination flashovers. The security stage is most important since it precedes the contamination flashover sufficiently. The three characteristics of the leakage current in the security stage are proposed as the inputs of a neural network model together with the operating voltage, and the relative humidity in order to determine the equivalent salt deposit density (ESDD) of the insulators. The comparison of the simulated and actual (measured) results demonstrates that the ESDD prediction model has a very low relative error if the training data and the testing data both come from the security stage. The application of this research results in (1) optimal ESDD prediction inputs and (2) sufficient pre-warning time before the ultimate contamination flashover.