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In the context of the construction project coalition (PC), the satisfaction of each participant is essential to harmonious working relationships which, in turn, is pre-requisite to improved project performance and successful project implementation. Therefore, there is a need to investigate mutual performance assessment between main participants of the PC, i. e. clients, architects and contractors. The principal aim of the research was to develop models of satisfaction for each participant based on a framework of mutual performance assessment. These allowed the interrelationships between participant performance and the satisfaction levels of other participants to be examined, leading towards developing a better understanding of the determinants of satisfaction. The development of the models involved performance and satisfaction attributes as independent variables and levels of satisfaction as dependent variables. Data were collected via a UK-wide questionnaire survey of clients, architects and contractors. Performance attributes represent characteristics of the performer that may influence satisfaction levels of the assessor. Satisfaction attributes represent characteristics of the assessor that may influence their own satisfaction judgements. The use of a singular or multiple measures of satisfaction levels was thoroughly considered. Subsequent analyses led to the decision to use a single measure of satisfaction, that is overall satisfaction (totsat) derived from one question in the questionnaire. Models of satisfaction were developed for each participant using both multiple regression (MR) and artificial neural network (ANN) techniques. While the MR technique was chosen because of its ability to predict levels of satisfaction, the ANN technique was applied because of the nature of the research problem which suggested that a somewhat more 'sophisticated' tool was needed. The reliability and robustness of the models were tested and confirmed using independent (hold-back) data, i. e. that which had not been used to develop / train the models. The models suggest that a capable client's representative and project architect are essential for higher levels of satisfaction. Therefore, the selection of these figureheads must be carefully considered. Additionally, the appointment of a contractor with an excellent track record is also crucial for enhanced satisfaction levels. Most importantly, clients must give considerable thought to the method of procurement. Here, it is suggested that long-term relationship-based procurement routes, such as partnering and strategic alliances may have advantages over traditional competitive tendering routes. A comparison of the models revealed that the ANN and MR models tended to highlight different variables, and that in terms of accuracy and consistency, the ANN models were marginally better than the MR models. For reasons of practicality, the MR models may therefore be preferred. In sum, the models developed could be used to predict satisfaction levels and to help improve performance and enhance levels of satisfaction. This ultimately will help to create a performance-cnhancing environment leading to harmonious working relationships between project coalition participants, and so encourage continuous performance improvement for the betterment of all involved.