This work presents a set of intelligent techniques aimed at analyzing and solving various issues regarding truck arrivals and stays at seaports. These techniques aim to optimize the truck arrival process, reduce dwell times, and alleviate congestion situations. The proposed techniques offer a comprehensive analysis of truck status at seaports, including the use of machine learning techniques to predict future situations, data visualization tools for a concise overview of current status, and simulation models to analyze behavior in hypothetical scenarios. All proposed intelligent techniques are integrated into a decision-support system, providing port management with detailed planning of truck arrival statuses. This enables the planning and optimization of port spaces to reduce truck waiting times and entry door congestion.