This study examines how machine learning (ML) and process analytical technologies (PAT) are being integrated in the food sector and how this has transformed production procedures. The techniques and instruments utilised for manufacturing's real-time monitoring and control fall under the category of process analytical technologies. Manufacturers may obtain more productivity, quality control, and operational insights by fusing these technologies with ML. Real-time process monitoring, predictive maintenance, quality assurance, and optimisation are made possible by this connection, which improves resource efficiency and allows for product customisation. However, for successful deployment, issues including data integration, model interpretability, and security must be solved. This essay explores the advantages, drawbacks, and issues that might arise from combining ML with PAT in the food sector.