Worldwide initiatives aim to facilitate urban transitions toward climate neutrality objectives through diverse urban planning and design methodologies. This paper focuses on approaches that integrate empirically-grounded tools to guide stakeholders and local authorities in achieving climate neutrality targets. Within this context, the paper explores the utilization of data analytics, machine learning, and key performance indicators for informed decision-making in urban planning and design. The paper explores some key performance indicators, in the context of sustainable development goals, recorded for European countries and analyses them utilizing machine learning techniques. Accordingly, the main indicators are identified.