The research presented in this doctoral thesis shows how the product development (PD) of Complex Fenestration Systems (CFSs) can be facilitated by computer-based analysis to improve the energy efficiency of fenestration systems as well as to improve the indoor environment. The first chapter defines the hypothesis and objectives of the thesis, which is followed by an extended introduction and background. The third chapter briefly suggests the PD framework which is suitable for CFSs. The fourth and fifth chapter refer to the detailed performance modelling of thermal properties (chapter 4) and optical properties (chapter 5) of CFSs. The last chapter concludes the thesis and the individual investigations. It is complicated to holistically evaluate the performance of a prototyped system, since simulation programs evaluate standardised products such as aluminium venetian blinds. State-of-the-art tools and methods,which can address interrelated performance parameters of CFS, are sought. It is possible to evaluate such systems by measurements, however the high cost and complexity of the measurements are limiting factors. The studies in this thesis confirmed that the results from the performance measurements of CFSs can be interpreted by simulations and hence simulations can be used for the performance analysis of new CFSs. An advanced simulation model must be often developed and needs to be validated by measurements before the model can be reused. The validation of simulations against the measurements proved the reliability of the simulations. The described procedures can be used at the initial stages of the PD to foresee the consequences of the innovation, and aim at the development by an iterative testing to meet the requirements. It was demonstrated that by improving the fenestration system, the overall building energy demand can be reduced by optimizing lighting, heating and cooling. The indoor environment quality can be improved by careful shading strategy and maximizing the use of daylight. The recent developments of the building simulation programmes enabled to perform annual, dynamic and climate based energy evaluation of CFSs. The case study of development of a window frame made of glass fibre reinforced polyester (GFRP) demonstrated that this composite material is suitable for window frames. A window with positive net energy gain (NEG) and a slim window frame was developed, by a combination of a low thermal transmittance and high load capacity of the material. Furthermore, the ventilated window, which uses the glazing cavity for ventilating the outside air that is supplied to the room, was investigated. By this concept some of the heat loss of the window can be regained by preheating the supplied air and thus increase the net energy gain of the window. However, the usage of the window for such a purpose is limited by the low heat recovery efficiency, which drops with the increase of the airflow. The heat balance of the ventilated window varies significantly from the heat balance of standard window. The theoretical heat balance of the ventilated window was defined in the study. In this thesis, properties of several shading systems were investigated including an analysis of the visual comfort. The simulations of daylight, lighting demand and glare were accomplished by ray tracing simulations in the software Radiance. The results from these investigations demonstrated that the performance of unique shading systems can be simulated, such as micro structural shading or light redirecting systems. It was illustrated that an advanced analysis is needed to evaluate a CFS, a simple evaluation, e.g. g - value or Uw - value, would not provide sufficient knowledge about the new properties. Bi-directional description of the optical properties of the shading system was used for investigation of lighting conditions and glare as well as NEG under different incident angles. The overall conclusion of the thesis is that it is possible to develop and optimize any CFS with the help of computer performance modelling. The PD methods can clearly identify the objectives of the investigation and set out the appropriate way to achieve the optimal solution.