The advent of the container traffic in maritime transportation has led during its 40-year long history to novel perceptions and operation planning requirements for the port container terminal. A major requirement in this respect refers to the efficiency of the operations in the container transfer between the different modes. The current study presents a methodology on the development of a forecasting tool to access the service demand patterns at a marine terminal on per day basis. A set of forecasting models was introduced and their implementation difficulties were explored. The main effort in this approach was to replicate the distribution of container arrivals/pick-ups before and after the scheduled voyage date of a vessel. A data-driven decision support system was developed to retrieve and to analyze the historic information captured at a major terminal of the U.S. East Coast for a period of 18-months. The evaluation of the current solution revealed a satisfactory fit of the forecasting model projections to the actually observed patterns. Due to the lack of a solid theoretical background, the approach is unfavorable to the use of applied statistical tests. In general the product should be seen as a management information system designed to assist the terminal activity planning and equipment management in conjunction with the coherent experience of the operating team.