Current efforts toward the necessary energy transition are predominantly focused on climate change mitigation in relation to decarbonization measures, mainly on the energy sector, but may not succeed in satisfying the goals of reaching the full sustainability of human activities, which should foster social equity, economic stability, and security of supply. Energy System Optimization Models, used as a key tool in guiding energy transition strategies through the formulation of energy scenarios, mostly focus on economic aspects and emissions reduction objectives only, completely neglecting the critical issues of the multifaceted “sustainability” concept. In response to that, the aim of this research is to develop an all-encompassing metric for evaluating the sustainability of decarbonization scenarios. It incorporates twelve key indicators pertaining to environmental, social, and security dimensions that are weighted and combined into a sustainability index (SI) for evaluating power sector technologies. The open-source TEMOA-Italy model is employed to create a baseline scenario and a decarbonization scenario. The computed evolution of the power sector is evaluated through a singular, multi-dimensional SI trend, enabling the monitoring of sustainability progress over time. The impact of alternative prioritization of the various sustainability factors is analyzed by exploring thousands of weights assigned to those factors within the SI. The obtained SI profiles are analyzed employing both unsupervised and supervised data analytics techniques, with the aim to extract and characterize the most representative patterns in terms of profile magnitude and trend. Eventually, explainable artificial intelligence (XAI) methods are implemented to understand the set of key indicators that mostly affect those two features of the SI profile. It turns out that the reliability of power system, geopolitical considerations, and land use play a pivotal role in influencing the SI trend and magnitude.