<p>The land use increase in urban areas and global climate change have an increasing impact on disasters, and several disasters threaten many regions of the world. The effectiveness of conventional analysis of urban location has become limited in the face of the dynamic structure of a constantly changing world. An appropriate multihazard methodology based on existing data and knowledge can produce an interactive and easy-to-understand map that allows the visualization of individual and combined risks. This study used GIS, machine learning, and multi-criteria decision-making in a hybrid structure and developed an effective analysis model for the location selection of urban areas. The developed decision support system was tested in districts of Gaziantep City, Turkey. These districts are exposed to earthquakes due to their proximity to fault lines. Forest fires occur due to the proximity of districts to forest areas and landslides due to their sloping land structure and heavy precipitation. Analysis for the selection of urban sites was carried out to minimize the disaster risk and protect natural, environmental, and cultural assets in these regions, which were heavily affected by the 7.8 and 7.6 magnitude earthquakes centered in Kahramanmaraş on 6 February and turned into ruins.</p>