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As supply chain channels physical, financial, and information flows as well as associated risks, a firm's supply chain information should be helpful in understanding and predicting its credit risks. Credit ratings, as an approximate but important measure of corporate credit risks, have been widely used by investors, creditors, and supply chain partners in their decision‐making. This study studies the role of supply chain information in predicting companies’ credit ratings. Using firm‐level supplier–customer linkages and corporate credit rating data, we develop a machine learning framework with gradient boosted decision trees to examine whether and what supply chain features can significantly improve the prediction accuracy of credit ratings, and what types of supply chain links have higher information content that positively affects the predictability of the supply chain features. We construct a firm's supply chain variables …