This building-level damage assessment applies a Geospatial Artificial Intelligence (GeoAI)-enabled remote-sensing workflow to rapidly identify visible conflict-related damage to buildings across Beirut and Mount Lebanon. The assessment was conducted by the United Nations Development Programme (UNDP) and complemented by records from the United Nations Department of Safety and Security (UNDSS) and the Lebanese Armed Forces (LAF) to ensure robust multi-source validation. The results were further validated through a comprehensive field verification exercise conducted in collaboration with the National Council for Scientific Research – Lebanon (CNRS-L). In addition, the assessment methodology, damage classification framework, and rubble volume estimation approach were jointly reviewed and validated with CNRS-L to ensure scientific rigor, methodological consistency, and alignment with national damage assessment standards. This fact sheet presents the core findings of the assessment, while the full report provides detailed datasets, methodology, validation procedures, and analytical results.