The calculation of a residential Energy Label in the Netherlands and the payback time of an energy refurbishment are often affected by various inaccuracies between theoretical and actual achieved energy consumption. Even if improvements are attempted on either of them, significant problems occur such as the accuracy of input data for the simulation or the large duration of sufficient measurements. According to the latest research, a significant uncertainty is stemming from the calculation of the space heating requirements. The goal of this study is to increase the input data accuracy for some of the most influential parameters for this calculation, focusing on those depending on the characteristics of the building envelope. These include the U-values of building elements, infiltration factors and the solar gain factors of the windows. To achieve this goal, an automated process is developed, where by calibrating an energy simulation model (BPS) of a house with a sample of actual measured data, an estimation of its real parameters can be produced. This is then used to verify its design, assess the efficiency of its building envelope and create the basis for estimating its yearly energy consumption. The measured data is originating from monitoring the Prêt-à-Loger house, a prototype refurbishment system designed with the intention to render the terraced houses of the Netherlands energy neutral. A sensitivity analysis is first conducted to estimate the relative importance of each parameter in terms of simulation error and energy. The process then succeeds on indicating some difference between live measurements and the simulation produced by the parameter values documented in the design. By treating these parameters as unknown, a model calibration process is set to find them, as in the case of an old house where material properties are lost or undocumented. The process is finally resulting on an adequate range of as-built parameters, validated against further measurements with an acceptable error.