The performance functions of large-scale complex structures are often implicit and nonlinear, which leads to problems such as high computational costs and low computational accuracy in reliability calculation. In this regard, a dynamic machine learning classifier surrogate model based on Monte Carlo simulation (DMLC-MCS) is proposed. The training sample points are generated by the Markov chain Monte Carlo (MCMC) method and numerical analysis to create the training sample dataset, and the surrogate model based on m…