Missing data, occurring in clinical trials due to various reasons, will cause information loss of the original data and reduce the robustness and validity of the research results. Therefore, missing data should be dealt with caution in clinical trials. This article introduces the causes and types of missing data, as well as several common methodological approaches to addressing the problem, in order to promote researchers' understanding and improve the quality of handling missing data in trials. Nevertheless, the best way to deal with missing data is to prevent or reduce data loss in clinical trials, rather than relying on post hoc statistical analyses.