LAUSR

8 The recent pandemic of COVID-19 has had severe impacts on healthcare services especially 9 the Food and Drug Administration for providing necessary drugs from appropriate suppliers. In 10 the current study, we aim to develop a data-driven model for sustainable-resilient supplier 11 evaluation. So, we identify the related criteria based on literature and experts and then calculate 12 their weights using Fuzzy-Bests-Worst-Method (FBWM). Afterward, the Fuzzy Inference System 13 (FIS) method is employed to evaluate the performance of the suppliers. Finally, three different 14 classification machine learning models are developed based on the supplier historical data in 15 every criterion and also the FIS output as the target column. This study identifies a suitable list 16 of sustainable and resilient criteria for supplier evaluation. Specifically, 22 criteria are identified 17 and categorized into three-dimension (economic, social, environmental, and resilient). The 18 results show that the case study managers pay more attention to ‘Responsiveness’ and ‘Ability’. 19 The two-stage FIS results indicate that 35 records are evaluated as very poor, 70 ones as poor, 20 98 ones as moderate, 90 ones as good, and 57 as very good ones. Other companies could use 21 the same model for their supplier selection decision-making to have a better decision for 22 selecting their potential suppliers.