EU's proposed revision of the EPBD (Energy Performance of Buildings Directive) contains a provision that residential buildings must achieve at least energy class E or higher by 2030. Furthermore, the objective is for all national buildings to achieve a netzero energy standard by 2050. According to the Swedish National Board of Housing, over 60% of Swedish multi-family buildings are classified within energy classes E, F, or G, which, in conjunction with the proposed revision of the EPBD, could result in a drastic increase in building renovations.By considering this scenario, it becomes relevant to investigate possibilities to optimize energy efficiency strategies on a case-study building, which is conducted in this study with digital simulation tools. Rhinoceros is the primary platform used to perform anenergy analysis and to use secondary plugins such as Grasshopper, Honeybee, Ladybug, and EnergyPlus. The last plugin mentioned generates a primary energy number for the building model, allowing modifications to the HVAC system and building envelope. Integrating DOE (Design of Experiments) and Descriptive Statistics methodologies facilitates building modeling and energy simulation, synchronized with a programmed script to produce statistical charts depicting the building’s energy performance. In compliance with the energy declaration of the case-study building, the structure is identified as a multi-family residence located at Östra Storgatan 81 in Jönköping on the real estate Censorn 7. Moreover, the year of construction was 1941 and the building currently possesses energy class E, which makes it suitable to simulate modifications to increase its energy performance.The simulation results indicate an upgrade in the building's energy class, advancing from class E to class C which is a two-step improvement on the EU energy classification scale. Specifically, the results demonstrate a decrease in the primary energy number from 110 [kWh/m2, year Atemp] down to 66.1 [kWh/m², year Atemp], reflecting a reduction of 40 [%] in energy use. Using different energy simulation engines in the analysis revealed marginal differences in the generation of primary energy numbers, which cross-verified the outcomes. In total, two energy simulation engines were employed alongside a comfort analysis. The results from the initial energy simulation engine were aligned with the findings from the comfort analysis, thus confirming the functionality of the script.While implementing the method, several challenges occurred such as the capability to accurately replicate the building’s geometry inside Rhinoceros. Another issue was to properly create an HVAC system with district heating inside Honeybee since each HVAC component needed to be customized to match an HVAC system with district heating. A third problem arose in finding certain material attributes required for Honeybee, as they were unavailable in product data sheets or through manufacturer inquiries. Despite these obstacles, the conducted strategy for energy simulation analysis has proved effective in illustrating the building's primary energy consumption.