The provision of adequate levels of thermal comfort in the indoor environments of buildings is constantly becoming of particular importance for the occupants of contemporary buildings. The energy-intensive processes of artificial conditioning have been established as the basic approach to the effort to create adequate comfort conditions, leading to the raise of energy consumption in buildings. The ability of contemporary buildings to provide thermal comfort in modern living environments while performing in an energy efficient manner has become a critical challenge.The seemingly conflicting objectives of provision of thermal comfort and maintaining the energy efficiency of buildings require an intelligent technological design approach in the context of an optimization problem.During the last years a variety of Artificial Intelligence (AI) based techniques and methodologies have been proposed in the literature in the context of investigating the issue of successful balancing indoor comfort levels for occupants and efficient energy consumption in buildings. Artificial Neural Networks (ANN) is a prominent technique of AI technology that has the potential to significantly contribute to the accomplishment of high standards in thermal comfort in buildings in an energy efficient and environmentally friendly manner.The thesis project will attempt to explore the theoretical framework of how ANN based building control systems apply to improve thermal comfort and maintain energy efficiency in contemporary buildings, by reviewing and filtering through reviewed studies from 2017 to 2022.The thesis will analyze the main motives and objectives of ANN model control application in buildings, evaluate the performance on thermal performance improvement and energy efficiency and present the key insights gained, critically discuss the critical challenges that need to be addressed, and finally highlight the future perspectives of the ANN based control system applications in buildings for accomplishing high standards of occupants’ indoor thermal comfort in an energy efficient manner.The findings of the thesis will show that the ANN based control systems that apply in the contemporary building infrastructures during the last years outperform the traditional control systems and have generally a significant potential to reduce energy consumption, as well as to provide a more consistent and personalized thermal comfort experience for occupants.Lastly, the thesis will conclude that AI and the ANN optimization models in particular may deliver better results in the future, provided that significant challenges are faced. Specific future perspectives and recommendations will be proposed, based on the conclusions drawn from the buildings analyzed in the papers studied.