Hurricanes are among the most devastating and costliest natural hazards. This devastating impact urged governments and policymakers to implement mitigation plans and strategies that can enhance the community’s resilience against hurricanes. A fundamental step to gauge the performance and effectiveness of these mitigations plans is to develop computational frameworks that can provide a probabilistic assessment of the resilience of the community. Therefore, this paper presents a framework to probabilistically estimate the resilience of residential wooden buildings against hurricane winds. The framework estimates the post-hurricane damage due to dynamic wind pressure and the impact of windborne debris using an engineering-based hurricane vulnerability. The building recovery function is then estimated by integrating the estimated damage with a building-level recovery model. By aggregating building recovery functions, the community recovery function is obtained. The Monte Carlo simulation method is used to account for uncertainties related to the hazard intensity, community vulnerability, and recovery process. The framework is applied to a residential neighborhood in Miami, FL. This framework can help decision-makers to compare current community resilience with target levels, identify the gap, and set strategies to improve community resilience.