One of the pillars of supply chain risk management is risk assessment and its aim is to analyze the risk. The first step to assess supply chain risk is identifying and classifying them. In this paper, after reviewing the literature and extracting supply chain risks, service supply chain risks  identified by focus group and Q-sort method. As the result 10 components of the most important risks as conditional characteristics in Rough modeling identified. Using Rosetta software, 5 set of rule were produced. According to extracted models among conditional attributes, market and financial risks were most important attributes. After completion of various models validation, the model by Conditional Mean/Mode fill and incompletes for complement data showed the highest reliability for predicting new observations.


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