The risk of adversaries instigating mass human migration, refugee flows and crowd formations in the battlespace1 requires mitigation because unexpected population movements can adversely impact the United States and partners’ freedom of operations abroad. As well, Information operations and physical events initiated by operations in an area may result in population activity patterns (second and third order effects/events). Even relatively small gatherings of non-combatants, especially at urban choke points can have repercussions impacting military operations which rely on predictable traffic flow on roads and infrastructure. Simulation in the field of Pattern of Life Analytics (PoLA) is critically important to the military because it may lead to improvements in predicting patterns of movement and other behaviors that are realistic, reliable, and repeatable among non-military populations. There is insufficient modeling of the political, economic and social conditions within the operational environment (OE) and their effects on combatants and noncombatants. Meanwhile, emerging connected device tracking technologies provide rich new data sources required to assess ongoing patterns of life activity levels (traffic patterns, work, shopping, pedestrian flow, refugee movement, crowd gatherings and so on). This paper describes a technique for representing migration of a civilian population in a way that is amenable to computation (i.e., simulation). The model firmly rooted in social science principles for: a) establishing a baseline of population location data, b) calculating populace mood changes based upon Political, Military, Economic, Social, Infrastructure, Information, Physical Environment, and Time (PMESII-PT) interventions, and c) forecasting timing and size of refugee flows and direction of their movements to, d) further model their external migration in Athena. As a result, the military decision makers can understand PMESII-PT impacts of non-combatant population movement in the battlespace. Lessons learned from this work could be used to simulate and predict non-combatant movement and identify potential impacts in the OE.