This study use machine learning (ML) to reveal the intrinsic economic specializations in different localities by analyzing a comprehensive dataset of economic indicators, such as gross added value (GVA) and revenue to the local budget. The results of our research demonstrate that machine learning algorithms may accurately detect both well-established and growing economic specializations, hence offering more profound understanding of regional economies. Moreover, supervised learning models exhibit the ability to forecast forthcoming economic patterns, so showcasing the predictive prowess of machine learning in economic analysis. Ultimately, this will assist policymakers in making well-informed decisions.