Today’s highly integrated supply chains are exposed to various types of risks that disrupt the normal flow of goods or services within a supply chain network. Since most of these individual risks are interconnected, a mitigation strategy to tackle one risk may result in the exacerbation of another. Given that the occurrence of one risk may cause a chain reaction, an important question arises: how to model risk dependencies in a supply chain and what factors are relevant in measuring supply chain dependencies? In the financial insurance literature, risk dependencies have been modeled using two approaches: (i) random variables, and (ii) copulas. This paper first reviews these studies to understand the dependency factors and their sources. Then, these models are extended for predicting and mitigating supply chain risks under dependencies. Finally, those models are applied to different supply chain network configurations.