The invention discloses a method for predicating contamination severity of insulator based on BP neural network and fuzzy logic, and belongs to the field of safety analysis and evaluation of power grids. The predication of the contamination severity of the insulator is essentially a state evaluation process of an uncertain and nonlinear system. The method is characterized in that the temperature, humidity, rainfall, wind speed and other basic factors are used as the basic input quantity to construct a BP neutral network predication model for the contamination severity of the insulator; the influence of attitude related to complex geographic position, air pressure ratio, freezing water conductivity and other factors on the contamination severity of the insulator is fully considered; the fuzzy logic compensation method is carried out to correct the evaluation result; the fuzzy mathematical method is carried out to comprehensively predicate the contamination severity of the insulator, and thus the problem of typical uncertainty of unclear factors influencing the contamination severity of the insulator during the evolution process can be solved; the method provides important scientific basis for determining the operation state of the power grid.