A fuzzy fault classification method of an electric transmission line includes the first step of determining the time of occurrence of a fault, the second step of computing fault input vectors, the third step of constructing fuzzy support vector machine FSVM dichotomy devices, the fourth step of training and optimizing the FSVM dichotomy devices, the fifth step of constructing a banding subsection subordinating degree function of a FSVM higher space, the sixth step of enabling the fault input vectors to be input into each FSVM dichotomy device to obtain a preliminary classification label, a decision function value and an initial subordinating degree of each FSVM dichotomy device, the seventh step of constructing and training a support vector regression (SVR), the eighth step of sending the decision function values and initial subordinating degrees into the SVR to obtain a final fault subordinating degree of a fault sample, and the ninth step of judging the final fault type according to the final subordinating degree. According to the fuzzy fault classification method of the electric transmission line, the fuzzy subordinating degree function is introduced, and therefore influences of noise points and isolated points on a SVM hyperplane structure are reduced; the SVR is adopted to perform correction on the preliminary classification labels obtained by the FSVM, the fault classification label is obtained accurately through fuzzification processing, regressive optimization processing and the like, and therefore the accuracy and fault tolerance for fault classification of the electric transmission line are greatly improved.