The article is based on the need for music education innovation in colleges and universities to optimize the traditional piano skill training through Monte Carlo algorithm. Taking the finger as the research entry point, based on the physiological structure of the hand, the reduced-density Monte Carlo method is used to carry out the mechanical design of the finger trainer and plan the finger training movement mode. Through kinematic simulation experiments to understand the feasibility of the piano finger training device in this paper. Analyze the error sensitivity of position and posture on the finger training device. Finally, the teaching experiment method is utilized to explore the training effectiveness of the Monte Carlo-based piano finger training device in this paper. This paper has good usability. When the position error of the mechanism varies in the range of -40mm~40mm, the position error gradually decreases in the X-axis and Z-axis, and the position error in the direction of Y-axis remains stable. The attitude error of the mechanism gradually increases with the increase of the X-axis rotation angle. The output accuracy gradually increases during the rotation from -5° to 5° around the Y-axis. The angular attitude around the Z-axis has no significant effect on the output accuracy. The two groups did not have significant differences in the four dimensions of piano playing skills before the experiment. After the teaching experiment, the experimental group was much better than the control group, and the posttest results of the two groups produced significant differences, and the pre-test and post-test results of the experimental group possessed very significant differences. The Monte Carlo optimization-based piano finger training device has a significant effect on the improvement of students’ piano skills.