Rare pediatric diseases often present significant diagnostic challenges due to their atypical manifestations and lack of familiarity among healthcare providers. Artificial Intelligence (AI) offers transformative potential in bridging diagnostic gaps, particularly in resource-limited settings. This review highlights the role of AI in identifying rare pediatric conditions through advanced algorithms, pattern recognition, and machine learning. By examining successful implementations globally, we explore the potential of AI to revolutionize pediatric diagnostics, address disparities in healthcare access, and improve outcomes for children. Challenges such as data bias, ethical considerations, and infrastructural barriers are also discussed, alongside recommendations for future research and integration strategies.