Insurgency emerges from many interactions between numerous social, economical, and geographical factors. Adequately accounting for the large number of potentially relevant interactions, and the complex ways in which they operate, is key to creating valuable models of insurgency. However, this has long been a challenging endeavour, as insurgency imposes specific limitations on the data that could speak to these interactions: quantitative data is limited by the difficulties of systematic collection in war, while qualitative data may include vague or conflicting insights from direct observers. In this paper, we designed a computational framework based on Fuzzy Cognitive Maps and Complex Networks to face these limitations. A software solution fully implements this framework and allows analysts to conduct simulations, in order to better understand the current dynamics of insurgency or test ‘what-if’ scenarios. Two approaches are presented to guide analysts in developing models based on our framework, either through a nuanced reading of the literature, or by aggregating the knowledge of domain experts.