Abstract— Fault location plays an important role in power systems. It is frequently used in transmission lines to reduce the system damage for growing electrical energy demand. However, the location estimation method itself is easy to be disturbed by different parameters and gives estimation errors. To solve this problem, this paper introduces a scheme that uses neuro fuzzy system (NFS) to locate all types of faults such as shunt faults, transforming faults, series faults and simultaneous faults in six phase overhead line (SPOL). This scheme has been performed on a 68 km, 138 kV, 60Hz, SPOL for all fault types by employing MATLAB software Simulink. Here, Haar wavelet transforms (HWT) are used to extract the current signals in order to evaluate the behavior and characteristics of higher frequency components. Then, the obtained HWT currents data are employed to construct the fault location scheme in SPOL based on NFS. The obtained experimental results confirm that by using the NFS, the maximum fault location error (MFLE) can be reduced by more than 10%. It can further reduce the maximum response time (MRT) for the operator to address the faults and ensure the power system reliability in the future. The test result executed in this investigation indicates that the NFS is resilient to wide changes in fault conditions, and it shows good performance and huge potential for location of faults in SPOL.