Climate-related disasters and recurring social crises disproportionately affect vulnerable populations in developing countries, including Indonesia as one of Asia's most disaster-prone nationn, lacks a validated, simulation-based adaptive social protection (ASP) model tailored to its institutional context. This article addresses that gap by developing and validating an ASP model for Lampung Province, Indonesia, a high-risk region with documented exposure to tsunamis, flooding, and elevated socioeconomic vulnerability. The study employs a sequential exploratory mixed-methods design: qualitative data from focus group discussions with 18 key informants were used to conceptualize causal structures, while quantitative simulation using Vensim PLE 16.1.1 was employed to test two policy scenarios. Simulation results demonstrate that rapid government response reduces community vulnerability within 12 simulation periods compared to delayed response, while community capacity building yields greater long-term resilience gains with accelerating recovery slopes that outperform government-centric responses. The model identifies infrastructure recovery, psychological stability, and economic diversification as the three most influential feedback variables. These findings contribute the first validated SD-ASP model for Indonesia and provide actionable policy recommendations for integrating adaptive social protection into Indonesia's national disaster management framework.