Globalization and technological advancements have increased the importance of transportation, leading to a rise in demand, especially in the logistics industry. This growth in transportation negatively impacts the environment, causing an increase in greenhouse gas emissions and air and sea pollution. Therefore, it is important to develop more efficient and sustainable transport models that reduce environmental damage while meeting logistics needs. Multimodal systems and transport optimization are key to balancing economic growth and environmental protection. Multimodal transport reduces transaction costs by working with a single service provider, but it is not always the most efficient or sustainable solution for the broader supply chain. Logistics service providers often prioritize the use of their own infrastructure, which can conflict with customer needs, especially regarding sustainability. Although multimodal transport utilizes standardized procedures and reduces administrative barriers, economic factors often outweigh environmental concerns. Despite the system's flexibility, coordination between different transport methods can cause delays. Therefore, better alignment between profitability and sustainability in transport decisions is necessary. Integral transport reduces transport time by optimizing cargo handling and minimizing delays during transitions between different modes of transport. The use of standardized units such as pallets and containers increases cargo safety, reducing physical damage and facilitating transfers between different vehicles. This system allows flexibility in choosing the most efficient transport mode for different segments of the journey, reducing costs and improving efficiency. In the long run, reduced labor and fuel costs, as well as fewer trips, make integral transport economically viable. Increased security and resource optimization also contribute to the sustainability and reliability of supply chains. The paper defines multimodal transport, lists its key characteristics, defines multimodal transport networks, analyzes the future and potential of multimodal transport, and assesses the cost-effectiveness of these two models.