Aiming at the premise that the current mainstream modeling method is based on the reliable test results, it is difficult to obtain an accurate information description problem between fault and test. A new test-based modeling method based on probabilistic generalized stochastic Petri net is proposed. This paper first compares the mainstream modeling method with the Petri net modeling method, clarifies the problems existing in the mainstream modeling method, and the reasons for selecting the generalized stochastic Petri net model; then introduces the probability theory into the generalized stochastic Petri net model, using the conditional probability of the model nodes obtained by the Bayesian network, and it is also the first combination of Bayesian network and generalized stochastic Petri net. Finally, a missile engine system is modeled to obtain the probability correlation matrix of faults and tests, and the test indicators are tested. The feasibility and accuracy of the proposed method are verified by comparing the original correlation matrix with the probability correlation matrix obtained in this paper.