Partial discharge (PD) is the main cause of premature failure for the turn-to-turn insulation system in the inverter-fed motor. The prediction of PD inception voltage (PDIV) for the turn-to-turn insulation plays a significant role in the insulation design of inverterfed motors. Therefore, a PDIV prediction method for turn-to-turn insulation based on the deep belief network (DBN) is proposed in this paper. Firstly, a PD simulation model is formulated, which is based on Townsend theory. The PDIV of different simulation parameters for the turn-to-turn insulation is calculated. Secondly, the influence factors of PDIV on the turn-to-turn insulation are analyzed. The DBN is implemented to mine the non-linear relationship between the influence factors and the PDIV. Furthermore, the effectiveness of the proposed method is evaluated by simulation analysis and experiment. Finally, the principal influence factors of the turn-to-turn insulation are investigated by the mean impact value algorithm. The case study demonstrates that the max relative error of the proposed method is 5. 9% . It provides a novel idea for the condition assessment and insulation design of inverter-fed motors.