This report builds on earlier RAND research (e.g., Understanding and Influencing Public Support for Insurgency and Terrorism, 2012) that reviewed and integrated social science relevant to terrorism and insurgency. That research used qualitative conceptual causal models called ⁰́factor trees⁰́₊ to identify the factors that contribute to various aspects of terrorism or insurgency at a slice in time and how the factors relate to each other qualitatively. This report goes beyond the conceptual and qualitative by specifying a prototype uncertainty-sensitive computational model for one of the factor trees from the earlier research, one that describes public support for terrorism and insurgency. The authors first detail their approach to designing such a model, emphasizing the challenges they encountered in assigning mathematical meaning to the factor tree⁰́₉s numerous factors and subfactors, identifying suitable ⁰́₋building block⁰́₊ combining algorithms, and the uncertainty in their values and the relationships among them. They then describe how they implemented the model in a high-level visual-programming environment, show how the model can be used for exploratory analysis under uncertainty, and discuss their initial experience with it. Methodologically, the work illustrates a new approach to causal, uncertainty-and-context-sensitive, social-science modeling. It also illustrates how such models can be reviewable, reusable, and potentially composable.