Natural disasters, such as earthquakes and floods, can significantly impact the capacity of responsible organizations due to damage to infrastructure and a lack of reliable information. In the aftermath of such events, relief operations must be well-prepared to quickly and effectively meet the needs of affected individuals to create a secure environment. In this study, we aimed to assess the seismic risk of metropolitan regions in Mashhad, Iran. Given the complex and uncertain nature of this topic, employed the Analytic Hierarchy Process (AHP) to determine the most effective indices for estimating earthquake damage and classifying urban zones. The Black Hole Intuitive Fuzzy C-Mean (BH-IFCM) algorithm was then applied to zone the seismic risk in 13 districts of Mashhad City. The fuzzy model and intuitive fuzzy algorithm were used to evaluate and zone sensitive regions, and the optimization technique of Black Hole updated with the super-chaos method was utilized to develop optimal solutions. The results of our analysis achieved a classification accuracy of 97.34% for Mashhad City and 96.73% for Bam City.