This paper focuses on the influence of detailed engineering maturities on offshore engineering, procurement, and construction (EPC) project procurement and construction cost performance. The authors propose a detailed engineering completion rating index system (DECRIS) to estimate the engineering maturities, from contract award to beginning of construction or steel cutting. The DECRIS is supplemented in this study with an artificial neural network methodology (ANN) to forecast procurement and construction cost performances. The study shows that R² and mean error values using ANN functions are 20.2% higher and 19.7% lower, respectively, than cost performance estimations using linear regressions. The DECRIS cutoff score at each gate and DECRIS forecasting performance of total cost impact were validated through the results of fifteen historical offshore EPC South Korean mega-projects, which contain over 300 procurement cost performance data points in total. Finally, based on the DECRIS and ANN findings and a trade-off optimization using a Monte-Carlo simulation with a genetic algorithm, the authors propose a cost mitigation plan for potential project risks based on optimizing the engineering resources. This research aids both owners and EPC contractors to mitigate cost overrun risks, which could be continuously monitored at the key engineering gates, and engineering resources could be adjusted per optimization results.