The 2023 Turkey-Syria earthquake, a catastrophic Mw7.8 event, caused over 44,000 deaths and 160,000 building collapses. Traditional methods for assessing earthquake damage are subjective, labor-intensive, and limited by site accessibility and high-resolution imagery availability. This study proposes a multi-class damage detection (MCDD) model that integrates multiple remote sensing variables to assess building damage. The model combines amplitude dispersion index (ADI) and damage proxy (DP) maps from Synthetic Aperture Radar (SAR) images, normalized difference built-up index (NDBI) changes from optical remote sensing images, and peak ground acceleration (PGA). This approach characterizes damage on both large tectonic and individual-building scales. The MCDD model outperforms traditional methods using only DP by 11.25% in performance, effectively sorting different damage levels into no damage, slight damage, and serious damage. The study demonstrates the potential of integrating multiple remote sensing indices to enhance the accuracy of earthquake damage assessment, aiding rescue and recovery efforts.The 2023 Turkey-Syria earthquake, a catastrophic Mw7.8 event, caused over 44,000 deaths and 160,000 building collapses. Traditional methods for assessing earthquake damage are subjective, labor-intensive, and limited by site accessibility and high-resolution imagery availability. This study proposes a multi-class damage detection (MCDD) model that integrates multiple remote sensing variables to assess building damage. The model combines amplitude dispersion index (ADI) and damage proxy (DP) maps from Synthetic Aperture Radar (SAR) images, normalized difference built-up index (NDBI) changes from optical remote sensing images, and peak ground acceleration (PGA). This approach characterizes damage on both large tectonic and individual-building scales. The MCDD model outperforms traditional methods using only DP by 11.25% in performance, effectively sorting different damage levels into no damage, slight damage, and serious damage. The study demonstrates the potential of integrating multiple remote sensing indices to enhance the accuracy of earthquake damage assessment, aiding rescue and recovery efforts.