This systematic review of allergen cross-reactivity provides a comprehensive overview of the latest advancements in the field, focusing on the translation of basic concepts into clinical relevance. The review highlights the importance of molecular allergology in improving diagnostic accuracy, therapeutic stratification, and patient management. Key areas of progress include taxonomic advances, translational and diagnostic advancements, conceptual advances, and therapeutic advances. The review emphasizes the role of computational tools and host immune responses in understanding cross-reactivity mechanisms. It also discusses the challenges and unmet needs in the field, such as the limited availability of molecular allergens for in vitro diagnostic use and the need for better standardization and automation of multiplex methods. The authors conclude by highlighting the potential of artificial intelligence and machine learning in advancing predictive medicine for allergies and immunology.This systematic review of allergen cross-reactivity provides a comprehensive overview of the latest advancements in the field, focusing on the translation of basic concepts into clinical relevance. The review highlights the importance of molecular allergology in improving diagnostic accuracy, therapeutic stratification, and patient management. Key areas of progress include taxonomic advances, translational and diagnostic advancements, conceptual advances, and therapeutic advances. The review emphasizes the role of computational tools and host immune responses in understanding cross-reactivity mechanisms. It also discusses the challenges and unmet needs in the field, such as the limited availability of molecular allergens for in vitro diagnostic use and the need for better standardization and automation of multiplex methods. The authors conclude by highlighting the potential of artificial intelligence and machine learning in advancing predictive medicine for allergies and immunology.