Tropical Cyclones (TCs) are the most destructive and persistent natural hazards in the global tropics and subtropics, including in the US. The impacts from a TC on the coastal region manifests in various forms, such as coastal storm surge, inland flooding, and damages from high winds. However, quantifying risks from TCs using observations is challenging, in part due to the short length of the record during the satellite era. To address this, we have developed a Risk Analysis Framework for Tropical Cyclones (RAFT) to model the physical behavior of TCs and their impacts on the nation’s critical infrastructure. TC tracks are initially generated based on the ‘beta-advection’ method. Subsequently, a deep neural network approach is used to produce along-track intensities. Results reveal that the model well-reproduces the observed distribution of TC track locations, intensities and landfall probabilities. Next, a physics-based rainfall model is combined with TC tracks to produce precipitation at various TC locations. Further, the TC tracks are combined with storm surge, population, electric power, and infrastructure assessment models. Taken together, the RAFT is a unified framework to quantify the risk associated with TCs for the US East and Gulf coasts.