A supply chain (SC) is an adaptive and complex system of systems. Every actor of the chain may experience abnormal conditions (a disruption, distorted data, etc.) that may lead to negative effects on the performance. It’s important for a company to know how different functional and physical subsystems react face to risk events. Modeling is an effective approach to capture the complexity of the supply chain behavior. In this article, we propose a modeling framework that has the advantage to capture supply chain behavior under risk. It is based on a meta-model that uses the SCOR model as a basis. It defines a set of generic constructs that provide flexibility and modeling ease for supply chain practitioners. The constructs are structured into organization and execution constructs. The organization constructs capture the different functionalities of supply chain actors, while the execution constructs capture various ways of execution of supply chain actors’ functionalities. An automotive parts supply chain is modeled to illustrate the proposed framework. The originality of this framework is two-fold: it provides SC practitioners with a library of building blocks that support modeling scenarios and it facilitates the inclusion of SC risk management issues at the modeling phase.