The growth in the number of logistics platforms served by road, rail, waterway, and sea is a logical consequence of the extensive and rapid development of merchandise trade in a globalized economy. Transportand logistics are part of the same activity chain that allowsgoods to be transported to their destination. Dependent on the requirements of their customers and suppliers and subject to strong competition,companies in this sector must manage challenges concerningdeadlines, flexibility, and diversity of goods,while handling other risks associated with transport and logistics. The Bayesian approach, proposed inthis paper, covers all the steps necessary to implement decision support solutions for risk managementand control, starting from the identification of risks and the preparation of intervention to the conductingof various operations in crisis In this work, the predictionand the control of the road risks are conductedusing the influence diagram method, whose final objective is the optimization of the logistics function.After identifying and analyzing the different risks, the Bayesian networks (BNs) are initially used to modelthese risks and to prevent the various challenging situations from taking place in the logistics chain. Asa second step, we use the influence diagram as a tool for the decision-making procedure. Finally, a casestudy is presented to highlight the substantial contribution of this tool to controlling road risks whiletransporting goods.