Engineering activities can sometimes be affected by individual risk factors, but they can also be affected by multiple risk factors combined. However, existing studies rarely examine whether multiple risk factors superimposed on a particular activity result in superposed or non-superposed effects. To some extent, these effects may influence the accuracy of project managers’ decision-making when handling risks. By introducing the Bayesian Network (BN) into the process of multi-factor superposition influence analysis of project schedule uncertainty, this research expounded on the construction and implementation of the Bayesian Network diagram of project schedule risk. Based on the Bayesian Network concept, this research developed a Bayesian network-based engineering schedule risk detection model. Further, it was examined whether the influence produced by the superposition of risk factors equals the sum of the influences produced by each risk factor acting alone. It has been demonstrated through engineering examples that the model does not only clearly express project schedules but also has all the functions of a Bayesian Network, allowing it to serve as a platform for processing uncertain data. The case also revealed that when multiple risk factors are superimposed, the impact on the project schedule is not superimposed. These findings provide policymakers with a more comprehensive understanding of how to respond to risk.