It has been argued that traditional building simulation methods can be a slow process, which often fails to integrate into the decision making process of non-technical designers, such as architects, at the early design stages. Furthermore, studies have shown that predicted energy consumption of buildings during design is often lower than monitored energy consumption during operation.In view of this, this paper outlines research to create a user friendly design tool that predicts energy consumption in real-time as early design and briefing parameters are altered interactively. As a test case, the research focuses on school design in England. Artificial neural networks (ANNs) were trained to predict the energy consumption of school designs by linking actual heating and electrical energy consumption data from the existing building stock to a range of design and briefing parameters.