The rubber hand illusion is a phenomenon that involves perceiving a rubber hand as part of one’s own body. The occurrence of this illusion is evaluated by the subjective report and the proprioceptive drift, in which the position of the hand is shifted in perception. The proprioceptive drift and sense of body ownership are assumed to be related; however, some research results have cast doubt on this relationship. We built a deep neural network model to simulate the rubber hand experiment to investigate the principles behind proprioceptive drift. Our deep neural network model was trained using consistent multisensory data and tested with inconsistent data, such as the rubber hand illusion. The model successfully predicted proprioceptive drift, suggesting that simple predictive learning mechanisms can account for this phenomenon.