Unit load formation and load planning constitute key elements of contemporary logistics processes, influencing operational efficiency, transport safety, and the utilisation of cargo space. With the increasing complexity of logistics systems, the importance of software tools supporting these processes continues to grow. The aim of this study was to conduct a multi-criteria evaluation of selected software solutions for load planning and unit load formation. The study considered five software systems: Best Load, Cargo Optimizer Enterprise, CubeMaster, EasyCargo, and Goodloading. The evaluation was conducted using a weighted scoring method, encompassing eleven criteria grouped into three categories: functional, usability, and economic, with weights of 0.50, 0.30, and 0.20, respectively. Each system was assessed on a scale from 0 to 3, and the final score was determined as a weighted sum of individual scores. The highest final score was obtained by Goodloading (2.80 points), which performed best in both the functional (1.45 points) and usability (0.85 points) categories. EasyCargo ranked second (2.35 points), followed by CubeMaster (2.00 points) and Cargo Optimizer Enterprise (1.80 points), while the lowest score was recorded for Best Load (0.90 points). Within the functional criteria, the most influential factors were the ability to calculate axle loads and support for irregularly shaped cargo. In terms of usability, mobility and web-based accessibility were decisive, whereas in the economic category, the key aspects were cost levels and the flexibility of the licensing model. The results demonstrate that, within the scope of analysed sample, cloud-based solutions tend to outperform desktop systems in terms of functionality, usability, and economic flexibility. This advantage results from higher accessibility and the integration of advanced features, including the consideration of vehicle structural constraints and axle load calculations. The findings indicate that accurate representation of real-world loading conditions, combined with flexible system architecture, is a key factor influencing software effectiveness. The proposed approach provides a structured basis for the comparative evaluation and selection of logistics software solutions.