Date fruits are highly valued for their nutritional and economic importance, but are prone to various internal defects such as insect infestation, pit remnants, and foreign body contamination. Traditional inspection methods, such as manual sorting and metal detection, are inadequate for identifying internal anomalies, which pose risks to consumer safety and market acceptance. This chapter explores the application of X-ray technology in the postharvest processing of dates as a non-destructive and high-precision solution for quality assurance. It covers the fundamental principles of X-ray imaging, machine setup, and image analysis techniques, highlighting how artificial intelligence enhances defect detection and classification. Case studies from the Middle East and North Africa illustrate successful industrial implementation, demonstrating improvements in quality control, export compliance, and operational efficiency. Despite challenges such as high capital costs, technical complexity, and maintenance needs, X-ray systems offer substantial advantages over conventional methods. The chapter also discusses emerging trends, including hybrid imaging technologies, cloud-based analytics, and miniaturized systems for small-scale processors. These advancements underscore the growing role of intelligent X-ray inspection in building safer and more sustainable date supply chains.