 Decision curve analysis is a method to evaluate prediction models and diagnostic tests, but there is widespread misunderstanding about what they mean. This paper presents a step-by-step introduction on how to interpret decision curves by relabeling the y-axis as benefit and the x-axis as preference. A model or test can be recommended for clinical use if it has the highest level of benefit across a range of clinically reasonable preferences. This article was authored by Andrew J. Vickers, Ben van Kolster and U.W. Steyerberg.