Early identification of clinical deterioration in hospitalized children is essential to improve outcomes and prevent critical events. Over the past two decades, structured approaches such as pediatric early warning scores and rapid response systems have provided a framework for systematic risk detection in general wards. More recently, artificial intelligence and continuous monitoring technologies have begun to transform this field, offering the potential for more timely and accurate recognition of subtle changes in patient status. Despite these advances, challenges remain before seamless integration of these technologies into routine clinical decision-making can be achieved. This review explores the evolution of pediatric early warning systems and examines how emerging innovations may shape the future of predictive monitoring and clinical decision support in pediatric care.