In the current dynamic digital era, the increasing complexity of cybersecurity threats requires adopting a proactive and predictive attitude to enhance the process of risk management. Supply chain risk management (SCRM) is a critical case in which businesses deal with several external entities that make them susceptible to high potential threats and vulnerabilities. Integrating ML into SCRM with a focus on the shipment process can mitigate those threats and vulnerabilities. This study proposed a hybrid cybersecurity framework to embedded ML algorithm for the reason of anticipating and mitigating the risk. To recognising the technical limitations of strictly data-driven decision-making process, the framework integrates expert judgement from the fields of business and cybersecurity. By providing a practical framework for enhancing cybersecurity within supply chains in the form of a business intelligence tool that facilitates improved decision-making, this research contributes to SCRM theory by laying the foundation for ML integration.