Accurate prediction of the learning phase period ( LPP ) for slurry tunnel boring machines (STBMs) is essential for effective scheduling, cost control, and risk management in soft ground and mixed-face tunneling. Traditional models often oversimplify TBM performance and do not fully account for geological variability at the cutterhead depth. This study presents a predictive model that integrates ground conditions, represented...