In order to solve the problem that the risk assessment process of equipment procurement contract performance is affected by subjective factors, and the risk analysis method does not effectively explore the internal correlation mechanism between risks and results, a data-driven risk assessment method was proposed. By collecting historical data related to the performance of equipment procurement contracts, a contract risk database is formed; Then, the Apriori algorithm is used to mine the association rules of contract risk factors in the database, and the Bayesian network structure is constructed according to the association rules, so as to realize the visualization of the relationship between contract risk factors, and carry out risk analysis and problem prevention accordingly. Finally, a data-driven Apriori-RMM risk value calculation method is proposed, which ranks the risk of individual factors and evaluates the overall risk of the contract. The case study verifies the feasibility and effectiveness of the model.