As terror groups proliferate and grow in sophistication, a major international concern is the development of scientific methods that explain and predict insurgent violence. Approaches to estimating a group’s future lethality often require data on the group’s capabilities and resources, but by the nature of the phenomenon these data are intentionally concealed by the organizations themselves via encryption, the dark web, back channel financing, and misinformation. Here we present a statistical model for estimating a terror group’s future lethality using latent variable modeling techniques to infer a group’s intrinsic capabilities and resources for inflicting harm. The analysis introduces two explanatory variables that measure a terror group’s underlying capabilities and resources. These variables are strong predictors of lethality and raise the overall explained variance when added to existing models. The explanatory variables generate a unique early warning signal of an individual group’s future lifetime lethality based on just a few of its first attacks. Relying on between the first 10-20 attacks or the first 10%-20% of a group’s lifetime behavior, our model explains about 60% of the variance in a group’s lifetime lethality as would be explained by a group’s complete lifetime data. The model’s robustness is evaluated with out-of-sample testing and simulations. The findings’ theoretical and pragmatic implications for the science of human conflict are discussed.