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Design-build (DB) project success may be operationalised into 11 performance metrics. 65 factors that may affect DB project success are identified. Using data from 33 DB projects, correlation analysis shows that there are several factors that affect each performance metric significantly. Artificial neural network (ANN) technique is used to construct the models to predict project performance, and these models are tested using data from five new projects. This study finds that six performance metrics can be predicted with a reasonable degree of accuracy: project intensity; construction and delivery speeds; turnover, system and equipment quality. The key variables that affect project performance may be attributed to both contractors and clients. To ensure project success, contractors should have adequate staffing level, a good track record for completion on budget, and ability in financial management and quality control …