Simulation‐based serious games offer hands‐on experiential learning but often remain reactive and proprietary, limiting broader adoption and deeper engagement with core industrial‐engineering methods. We introduce LionSim, a Python‐based discrete‐event simulator that transforms multi‐echelon supply‐chain modeling into an interactive serious game. LionSim’s engine supports four mostly commonly studied network topologies: serial, convergent, divergent, and fully networked. Furthermore, key decision making for inventory, pricing, and demand forecasting are embedded in modules so that learners can extend or enhance these policies. At present LionSim supports reorder‐point and order‐up‐to inventory policies, cost‐plus and dynamic pricing, and simple moving average and exponential moving average forecasting. Through a unified Instructor Configurator, educators define scenario parameters including topology, demand and lead‐time distributions, policy settings, cost rates, and narrative assignments. Students engage via role‐based dashboards offering real‐time feedback on inventory, backorders, forecasts, and cost KPIs. LionSim logs rich time‐series data, underpinning post‐session analytics exercises in distribution fitting, control‐chart analysis, regression, hypothesis testing, and forecast‐accuracy evaluation. Future work will focus on piloting LionSim in real classroom settings and conducting formal usability evaluations to validate its educational impact and refine the platform. In the future LionSim will be made into as an online, multiplayer platform with multi‐product support, enabling scalable, data‐driven learning across distributed engineering teams.