Reliable and accurate fault location technology is very important for the stable operation of MMC-HVDC transmission system. Aiming at the difficulty of locating high-resistance ground faults, this paper proposes a method for locating single-pole ground faults of transmission lines based on wavelet packet energy entropy (WPEE) and deep belief network (DBN). By analyzing the fault information contained in the fault waveform under different conditions, the wavelet packet energy entropy is used to extract the deep fault features in the double-ended fault voltage waveform and construct a new feature matrix. Based on the new feature matrix, a DBN model is constructed by particle swarm optimization (PSO) algorithm on the matrix’s model parameters, and finally the DBN regression mechanism is used to achieve accurate fault location. In this paper, the electromagnetic transient simulation software PSCAD/EMTDC is used to build a ± 250 kV double-ended MMC-HVDC system model and simulate single-pole ground faults with different positions and different transition resistances on the line. In order to test the localization performance of the proposed model, the proposed method will be compared with the fault localization method based on support vector machine (SVM). Experimental results show that this method can accurately and reliably locate the DC-side single-pole ground faults with a resistance of up to 4 000 Ω at a low sampling frequency of 20 kHz.