A method for evaluating the uncertainty of amplitude-frequency characteristics of pressure sensors is proposed. Firstly, the probability density distribution of the pressure sensor model parameters was calculated based on the kernel density estimation method, and the pseudo-random number conforming to the probability density distribution was generated by the acceptance-rejection method. Then, an adaptive Monte Carlo iteration convergence threshold optimization method is proposed to accurately estimate the optimal iteration number. Finally, based on the optimal number of iterations, the adaptive Monte Carlo method is used to evaluate the uncertainty of the amplitude-frequency characteristics of the pressure sensor, and the optimal estimate value, the standard uncertainty and the uncertainty interval under the given confidence probability are obtained. The performance of the proposed method is verified by the uncertainty simulation of the amplitude-frequency characteristics of the pressure sensor. The results show that the mean and maximum absolute errors of the uncertainty evaluation results of the pressure sensor amplitude-frequency characteristics obtained by the proposed method are 8. 837×10 -5 and 5. 103×10 -3 , respectively, reduced by about 55% and 76% compared with Monte Carlo method (100 000 tests), and reduced by about 67% and 79% compared with adaptive Monte Carlo method, respectively, indicating that the proposed method can effectively evaluate the uncertainty of the amplitude-frequency characteristics of pressure sensors.