This master’s thesis explores the application of Modeling and Simulation (M&S) techniques in military operations involving Forward Arming and Refueling Points (FARP). FARPs play a crucial role in supporting aircraft operations by facilitating deep penetration into enemy territory and ensuring sustained presence in the Area of Operation (AOO). Due to the limited reach of aircraft, FARPs often become essential for accessing the AOO. Logistical units that are responsible for establishing FARPs, face the challenge of timely deployment, as joint air operations planning is complex and time-consuming. M&S is employed to enhance the efficiency of FARP planning processes for military helicopters.M&S allows for the testing of various solutions without the need for physical experiments, thereby enabling the exploration of different options during the planning phase of FARP operations. The Information Systems (IS) framework is utilized to create a theoretical knowledge base, forming the foundation for developing a M&S product tailored to the requirements of FARP operations.This master’s thesis utilizes the Fuzzy Cognitive Mapping (FCM) method to construct a model of FARP operations, while employing Monte Carlo Simulation to quantify associated risks and discrete event simulation to simulate the time aspects of such operations. The outcomes include a Python-based simulation program that interprets real-world map images, simulates FARP operations, and generates data such as helicopter fuel consumption and FARP survival probability.Although the simulation program has limited functionality, it demonstrates the potential of M&S to support decision-making processes for FARP commanders, which can enhance the overall efficiency of the FARP planning process. This is shown by a Spearman correlation test and Student's t-test, which revealed significant relationships among different elements of the model, reflecting the dynamics observed in real- world FARP operations. Further enhancements can be made to the simulation program by incorporating additional dynamic elements of the model.