This paper presents a fuzzy-logic technique for fault classification in a series compensated transmission line. The proposed method uses the samples of three line currents for half cycle duration to accomplish this task. Daubechies wavelet “dB4” is used with single level decomposition. The features of the line currents are extracted using discrete wavelet transform. The wavelet decomposition coefficient are divided into three bands to calculate the wavelet singular entropy of every frequency band to obtain the characteristics of the different failure. The extracted features are applied as inputs to the fuzzy logic for fault classification. To evaluate the feasibility of the proposed technique, it is tested on a 500 kV, 300 km transmission line for all the ten types of fault using Matlab. Simulation result indicates that the proposed approach has a good performance and it won’t be affected by fault resistances, fault inception angle, faulty types and fault distances at different TCSC firing angles.