It is necessary to bring global optimization in covering algorithm to improve its precision of classification.So a probabilistic model of covering algorithm is put forward in this paper.Firstly,the covering algorithm is ameliorated to kernel covering model(Gaussian function is the kernel function),then a kind of finite mixture probabilistic model for kernel covering model is introduced according to the probabilistic meaning of Gaussian function.Finally,the global optimization calculation is inducted based on maximum likelihood theory and Expectation Maximization Algorithm.Therefore,the algorithm optimizes the covering network broadens the application domain of covering algorithm and improves its robustness.The experimental results show that the optimized probabilistic model of covering algorithm can improve the accuracy of classification.