Scientific literature about energy retrofit focuses on single buildings, but the investigation of whole building stocks is particularly worthy because it can yield substantial energy, environmental and economic benefits. Hence, how to address large-scale energy retrofit of a building stock? The paper handles this issue by employing a methodology that provides the robust energy assessment of building categories. This is denoted as SLABE, “Simulation-based Large-scale uncertainty/sensitivity Analysis of Building Energy performance”. It was presented by the same authors to address the energy retrofit of a building category and is here enhanced to investigate a whole and heterogeneous building stock that includes various categories. Each category is represented by a Representative Building Sample (RBS), which is defined through Latin hypercube sampling and uncertainty analysis. Hence, optimal retrofit packages are found in function of buildings’ location, intended use and construction type. Two families of optimal solutions are achieved. The first one collects the most energy-efficient (and thus sustainable) solutions, among the ones that produce global cost savings, thereby addressing the collective perspective. The second one collects cost-optimal solutions thereby addressing the private perspective. EnergyPlus is employed as simulation tool and coupled with MATLAB® for data analysis and processing. The methodology is applied to a significant segment of the Italian public administration building stock, which includes several building categories depending on location, use destination and construction type. The outcomes show huge potential energy and economic savings, and could support a deep energy renovation of the Italian building stock