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Supply chains are networks of logistical facilities such as suppliers, manufacturers, warehouses, distributors, and retailers. These facilities facilitate the movement of raw materials, intermediate products, and finished products. Disruptions in supply chain logistics can lead to shortages ranging from negligible to devastating. For instance, drug shortages can have negative economic and clinical impacts on patients. To effectively assess the risk of supply chain shortages, a method that can represent the supply chain in a suitable format for decision-making analysis and can be automated is necessary. In “A Quantitative Approach to Assess the Likelihood of Supply Chain Shortages,” we defined a methodology to measure the probability of a supply chain’s throughput failure. Based on this methodology, we created the SUpply chain Probabilistic Risk Assessment (SUPRA), a software tool that quantifies the probability of supply chain shortages, as presented in this paper. Using facility failure and flow information, SUPRA outputs the supply chain failure probability and importance measures of the supply chain facilities. We can generate a shortage risk profile from the results. The shortage risk profile, importance measures, and quantified supply chain failure probabilities can inform decision-makers to mitigate and manage supply chain shortages.