 Missing data may seriously compromise inferences from randomized clinical trials, especially if missing data are not handled appropriately. The analysis of trial data with missing values requires careful planning and attention. We present a practical guide and flowcharts describing when and how multiple imputations should be used to handle missing data. This article was authored by Janus Christian Jacobson, Christian Gludd, J. R. N. Wetislev, and others.