Therefore, this paper looks at the ways in which predictive analytics has the potential to revolutionize the design of smart city systems through IoT and the application of machine learning for real-time decision-making. Combined with the growth of complexity in urban environments, predictive analytics can enhance several aspects of life in cities, such as traffic, safety, power supplies, and emissions. Abundant data from the IoT devices, along with enhanced analytical models make predictive analytics a useful tool in directing the city administrators’ operations. The paper outlines the major applications, data handling techniques, and real-time analysis paradigms required to incorporate prediction functionality into city systems. It also tackles issues like data privacy, when it is expandable and when and where it cannot work due to technical issues and other useful topics like blockchain, quantum computing, etc. These results indicate that there is great potential for the usage of predictive analytics to build progressive, cost-effective, and robust smart cities.