High penetration of distributed generation (DG) units will have unfavorable impacts on the traditional fault location methods because the distribution system is no longer radial in nature and is not supplied by a single main power source. This paper presents an automated fault location method using radial basis function neural network (RBFNN) for a distribution system with DG units. In the proposed method, the fault type is determined by normalizing the fault currents of the main source and the fault location is determined by developing two RBFNNs. The first RBFNN is used for determining the fault point distance from each source and the second RBFNN is used for identifying the exact faulty line. Several case studies have been made to verify the accuracy of the proposed method for fault diagnosis in a distribution system with DGs. Results showed that the proposed method can accurately determine the location of faults in a distribution system with several DG units.