The built environment plays a crucial role in global decarbonization efforts, yet buildings remain a major contributor to energy consumption and CO₂ emissions. Retrofitting existing buildings is essential to decrease the environmental impact of the construction sector but also for mitigating energy poverty, which affected 10.6% of the European population in 2023. This study proposes a multi-objective and multi-disciplinary methodology for optimizing the energy retrofit of a social housing building. The approach integrates parametric modeling, energy and daylight simulations, and evolutionary optimization algorithms to enhance building performance while considering economic and environmental constraints. The optimization is structured in two phases: a first optimization of the building envelope focusing on passive strategies and a second one specifically on the shading system, taking into account the increasing energy consumption for cooling. Results demonstrate that the optimized building achieves an 86% reduction in heating energy consumption and a 41% decrease in cooling energy consumption. The methodology effectively balances energy efficiency, renovation costs, and CO₂ emissions while ensuring daylight availability and occupants’ comfort. By utilizing mostly open-access parametric tools, the approach promotes accessibility and broader adoption. This study highlights the potential of multi-objective optimization in retrofit design, offering valuable insights for researchers, policymakers, and practitioners committed to sustainable building renovations.