In order to increase the urban resilience of disaster-prone areas in developing countries such as Türkiye, it is necessary to primarily ensure sustainable development while reducing the disaster risks of the physical structure. In this context, there are important problems in many categories such as physical, economic, social, environmental, legal, and institutional, planning and design, and technological. However, within the scope of this thesis, the focus has been on the decision-making problem in determining urban transformation strategies. In this context, the purpose is to develop a decision-making model, based on multi-criteria decision-making methods, which can be used by the responsible institutions for urban transformation in disaster-prone areas, and to carry out a pilot study on the working process of the model. For this purpose, the results of this research were evaluated with three hundred indicators/criteria contained in the literature, legislation, and urban transformation practice, and by using five decision alternative typologies for urban transformation processes [(1) Total Design Model, (2) All-of-a-Piece Model, (3) Piece-by-Piece Model, (4) Plug-in Model, (5) Plot-by-Plot Urban Transformation]. For this evaluation, the number of indicators was reduced by conducting a survey with institutions and a case study within the Aktepe-Emrez Districts Urban Transformation Project with twenty indicators identified as critical indicators after the survey analysis was tested with the officials of the relevant departments and the results were evaluated. The aim is to use the INTEMUS method, developed by using the DEMATEL and ENTROPI methods, based on the determination of criteria weights, developed on Microsoft Excel software, and the PROMETHEE and COPRAS methods, based on the ranking of decision alternatives, as a decision-making method that can be implemented by responsible institutions for urban transformation. Keywords: Resilience, Disaster Management, Hazard Mitigation, Sustainability, Sustainable Urbanization, Urban Transformation, Multi-Criteria Decision-Making.