Residential buildings consume a considerable amount of energy, but regularly such buildings are considered to possess a large potential for reducing their energy demand without neglecting the required comfort levels for occupants. There are several, in-part very different approaches that address the reduction of energy use in buildings. One approach is the so-called performancebased approach, which regularly requires the application of sophisticated simulation tools to evaluate buildings. The results of this approach can help to approximate optima regarding lowest cost and energy saving. However, given the level of detail and the extensive structure of state-of-the-art simulation tools, the performance-based approach often is time-consuming and cost-intensive. One alternative to this approach is the so-called prescriptive approach. This approach can be associated with less complexity in comparison to the performance-based approach. The main idea of this approach is to define levels for prescriptive performance data of buildings that can be influenced in early design stages. As such, it can provide valuable support to architects, who can use the approach to roughly estimate the performance of buildings without performing advanced calculations or simulations. In this context, this approach could be beneficial to improve the energy performance of buildings in regions and settings, where adopting the performance approach faces obstacles such as lack of resources, or large time and cost pressure. The main objective of this master thesis is to create a prescriptive building energy index which could be used as an instrument to determine the future buildings energy demand during the early stages of the design process. Thereby, the created index is based on the results of a linear regression model. This model is the result of extensive simulation efforts of a large set of buildings. The chosen building sample was based on the idea of representing the majority of residential buildings in the Gaza strip. The linear regression analysis is used to identify the most influencing descriptive building quality parameters on selected aspects of the building performance. This master thesis is thereby focused on overheating and cooling energy demand, the (simulated) cooling energy demand results of the building sample were used in the created linear regression equation, and utilized to generate a reference for the index. As compared to the outcome obtained from the simulation, the results show that buildings, which comply with certain characteristics, can achieve high energy efficiency levels (in these specific climatic boundary conditions). The results reveal that multiple performance indicators can be almost predicted interchangeably, as the overheating indicator was found to be highly correlating to the cooling energy demand of buildings. The results also prove that setting a future target regarding enhancing thermal characteristics of the current state of buildings would result in achieving apparent reductions in cooling demand requirements, as geometric and semantic properties of fenestration / glazing materials were found to be crucial within such context. While incorporating the current construction practices in addition to potential future enhancement targets, the created index could serve as a valuable indicator tool for architects, designers and engineers during the early stages of the design process.