Modern cities pose complications that are becoming increasingly more challenging to urban planners, resource managers, and policymakers. As the cities expand and evolve, they throw down for the demand for more effective and sustainable ways of meeting ever-increasing requirements. This chapter discusses some challenges by which AI-powered predictive analytics will provide solutions in improving the quality of urban living. It provides an overview for implementing AI predictive models in critical urban sectors, such as traffic management, energy distribution, public safety, and environmental sustainability. In addition, a detailed implementation blue print and code framework for the AI-based traffic flow prediction application is discussed. This paper explores how transformative AI-powered predictive analytics can be by providing a few real-life case studies. Finally, the key criteria and future considerations for implementing AI-Powered Predictive Analytics in Smart Cities is discussed.