A new study uses machine learning to forecast container dwell times and pre-clearance needs at shipping terminals. Researchers implemented a classification system for cargo descriptions and deduplicated consignee records to clean historical operational data. These models help container terminals reduce unproductive moves. The result optimizes strategic planning for logistics practitioners.