Corporate ESG disclosure quality is a key condition to optimize industrial structure and a realistic path to reach sustainability performance. Based on the theoretical knowledge of Bayesian network model, the research program of corporate ESG disclosure quality and sustainability performance influence path is designed. According to the current status of enterprise development, 11 research variables are set, which contain explanatory variables, interpreted variables, and control variables. Mathematical statistics and Bayesian network modeling are adopted to parse the mutual influence mechanism between the two. In the forward Bayesian inference, the probability of enterprise sustainability performance being in a good state is 49.3%, and the probability of the explanatory variables being in a good state is increased to 58.7% by changing the state probability of other variables. In order to provide a comprehensive overview of the relationship, backward Bayesian inference was also performed, and when the probability of sustainability performance being in a good state was 100%, the probability of the board concurrent position being in a good state was the highest with a value of 72.3%. This study enhances the most effective corporate ESG disclosure quality control program for companies to maximize the possibility of sustainability performance.