Predicting outcomes to guide clinical care, decision making, and resource allocation is a challenging undertaking in chronic kidney disease (CKD). Many prediction models have been developed, but few have been appropriately externally validated and even fewer have been assessed to be usable in the clinical setting. This contributes to the currently infrequent use of existing prediction models. Patients with CKD are a particularly heterogeneous group with significant biological variability, making the development of useful prediction models even more challenging.