This thesis aims to explore the intricate dynamics of urban heat islands (UHIs), a critical concern exacerbated by the combined forces of climate change and urbanization. The primary objective is to develop an urban-scale model, leveraging advanced machine learning algorithms, capable of incorporating a wide array of variables. The study also endeavors to probe the influence of climate change on UHIs through a meticulous examination of historical climate data, seeking to identify any discernible trends that might be linked to the exacerbation of UHIs. Furthermore, the research sets out to assess the efficacy of substantial urban regeneration projects in mitigating the adverse effects of UHIs.