In this paper, we use accounting fundamentals to measure systematic risk of distress. Our main testable prediction — that this risk increases with the probability of recessionary failure, P(R|F) — is based on a stylized model that guides our empirical analyses. We first apply the lasso method to select accounting fundamentals that can be combined into P(R|F) estimates. We then use the obtained estimates in asset-pricing tests. This approach successfully extracts systematic risk information from accounting data — we document a significant positive premium associated with P(R|F) estimates. The premium covaries with the news about the business cycle and aggregate failure rates. Additional tests underscore the importance of the “structure” imposed through recessionary-failure-probability estimation. The “agnostic” return predictor that relies only on past correlations between the same fundamental variables and returns exhibits markedly different properties.