High rates of missing perpetrator information in political violence data poses a serious challenge for studies into militant group behavior and the microdynamics of conflict more generally. In this article we introduce multiple imputation (MI) as the best available method for minimizing the impact of missing perpetrator information on quantitative analyses of political violence, a method that can easily be incorporated into most quantitative research designs. MI will produce valid attributions when the reasons for missingness are known and can be controlled for using observed variables, rendering responsibility for unclaimed attacks, i.e., "missing at random" (MAR) – which we show is a reasonable assumption in the case of political violence based on current theory of militant group claiming. We lay out the logics and steps of MI, identify variables and data sources, and demonstrate that MI produced better results in the case of Pakistani Taliban’s response to drone strikes.