As a consequence of the supply chain management pursuit for efficiency, the organizations become more dependent on the suppliers of raw materials and more sensitive to their risk profiles. The Supply chain risk management (SCRM) objective is to understand and reduce the likelihood of disruptions. SCRM puts its effort in sharpen the notions of risk and reliability and tries to quantify them. The methodology used in this study can be used by managers to formulate supply chain risk management strategies and tactics that mitigate overall supply chain risks correlated with the most critical suppliers. This research is concerned with developing a Bayesian Network approach to model and to analyze supply chain disruptions associated with suppliers. The Bayesian Networks is a method of modeling the cause and effect of events and has proven to be a powerful tool under conditions of uncertainty. A case study is used to illustrate the application proposed to make the supply chain more reliable.