Global supply chains are currently facing major issues due to their complex nature. Thus, it has become even more important to enhance control and visibility along the supply networks. In this manner, blockchain technology offers a distributed ledger network comprised of stakeholders, giving them the opportunity to better communicate and be involved in each and every step of the supply chain. The increasing amount of data and difficulty in predicting key performance indicators (KPIs) are other challenges for organizations to manage effectively. Machine learning (ML) algorithms are deployed in order to handle large amounts of data by processing, analyzing, recognizing patterns, and making decisions. Despite the integration of blockchain and ML is still in its infancy, we provide various industrial applications in this study. There are certain benefits of blockchain-ML integration, such as enhanced transparency and improved data security, yet challenges remain to be overcome. Both academia and practitioners could refer to this review, as it helps explore the benefits and potential challenges of industrial implementation of the system architecture. However, further research is still needed as regards the blockchain-integrated ML application in more diverse sectors, with a focus on training people to adopt new technology knowledge and skills.