In the scope of environmental challenges, the increasing frequency and intensity of floods pose a significant threat to communities worldwide. Addressing this concern demands innovative solutions that integrate technology and data analytics. The flood prediction and warning system presented in this paper represents an earnest endeavor to contribute to the ongoing efforts in mitigating the impact of floods on vulnerable regions. The objective of the work is to prevent impacts of flood using machine learning algorithms. Enhancing flood prediction models through research has reduced risk, recommended policies, reduced the number of flood-related deaths, and reduced property damage. Providing information on the best models and illustrating the current state of machine learning models for flood prediction are the main contributions of this paper. Within the context of a thorough assessment and conversation, the performance comparison of ML models offers a thorough grasp of the various methodologies. Consequently, the most promising prediction method is presented in this work.