Generally, the safety management system (SMS) introduced in 1980 focuses on reducing the risk of potential injuries and fatalities in the construction industry. The key to considering the challenges of project safety management and risk assessment in the construction industry as a hazardous industry because of its peculiar nature is important. In line with this, this article aims at employing decision-making techniques to ensure the safety requirements of construction projects. Additionally, a questionnaire under fuzzy environments for identifying the candidate locations and strategies associated with each specific location was conducted. Also, the Empirical Bayesian (EB) approach has been considered to estimate the expected frequency of accidents. The objective of the novel proposed approach is to find the optimal safety project selection with respect to the economic indicators and time value of money under uncertain circumstances. For this purpose, a mathematical optimization model is proposed, and its efficiency is demonstrated by a numerical case study. The results of optimizing the mathematical model indicate that by modifying two factors, namely the safety level and uncertainty coefficient, several scenarios can be explored for cost reduction and a decrease in the number of construction projects. By maintaining a constant safety level of 1.37 (as determined by industry experts) and increasing the uncertainty coefficient from 0 to 0.2, costs decrease by a factor of 1.7, accompanied by a decrease in the number of construction projects by one unit. Furthermore, when the uncertainty coefficient is held constant at 0.2, costs can be reduced up to four times by reducing the safety level from 1.37 to 1. This decision-making framework can significantly contribute to minimizing building accidents and enhancing safety in construction projects.