The paper proposes a new methodology for utilizing drones and UAVs during natural disasters such as floods and earthquakes. Natural disasters represent some of the most devastating events imaginable, underscoring the critical importance of preparedness to swiftly aid affected individuals. While natural disasters occur with varying frequency across the globe, their occurrence can severely impede human communication and mobility within affected regions. Providing assistance and procuring necessary equipment become significantly challenging, compounded by the constrained time available for response efforts. The initial 72 h following a disaster is pivotal for rescue operations. Developing an optimal rescue plan from ground-level assessments proves impractical. This is where drones and Unmanned Aerial Vehicles (UAVs) come into play. With advancements in drone technology, it becomes imperative to devise intelligent strategies for their deployment during natural disasters. This paper endeavors to propose an intuitive methodology aimed at analyzing affected areas, providing optimized routes, and predicting safe zones through modern machine learning algorithms. The proposed methodology seeks to expedite the analysis of current conditions and enhance the efficiency and safety of rescue operations. Central to this project is the establishment of reliable communication between the two drones and the server, along with the development of efficient task allocation strategies for each drone. Additionally, the methodology includes an interactive user interface housing all the information communicated and computed by the system. In conclusion, the proposed methodology aims to streamline rescue operations during natural disasters by harnessing the capabilities of drones and UAVs. Through improved efficiency and informed decision-making, this approach endeavors to enhance the effectiveness of disaster response efforts, ultimately contributing to saving lives and mitigating the impact of natural disasters.