Acute kidney injury (AKI) leads to high rates of morbidity and independently increases mortality risk. Therapy for AKI is likely limited by the inability to reliably diagnose AKI in its early stages, and, importantly, small changes in serum creatinine may be associated with poor outcomes and severe AKI. Whereas AKI biomarker research seeks to identify more sensitive and timely indices of kidney dysfunction, AKI lacks physical signs and symptoms to trigger biomarker assessment in at-risk patients, limiting biomarker efficacy. Accurate models of AKI prediction are unavailable. Severity of illness (SOI) scoring systems and organ dysfunction scores (OD), which stratify patients by prediction of mortality risk, are AKI reactive, not predictive. Kidney-specific severity scores do not account for AKI progression, and stratification models of AKI severity are not predictive of AKI. Thus, there is a need for a kidney scoring system that can help predict the development of AKI. This review highlights the concept of renal angina, a combination of patient risk factors and subtle AKI, as a methodology to predict AKI progression. Fulfillment of renal angina criteria will improve the efficiency of AKI prediction by biomarkers, in turn expediting early therapy and assisting in creation of AKI-predictive scoring systems.