Artificial intelligence (AI) is a cutting-edge technology that is becoming an innovative tool in everyday clinical practice, particularly in neonatology. It not only facilitates diagnosis, but also supports therapeutic decision-making. In neonatology, AI applications are diversifying, ranging from simple monitoring to advanced technologies such as image recognition. This recognition can be used to determine gestational term in the case of poorly monitored pregnancies and to diagnose respiratory pathologies, such as Respiratory disease syndrome (RDS), which is common in premature newborns. Although clinical expertise is essential for making a diagnosis, AI offers a contributory role, particularly in situations where radiological interpretation is less straightforward. This work currently explores the potential of AI for the early detection of RDS, based on the use of a high-performance AI model and a database comprising radiological images of premature babies. In the long term, this approach aims to design an AI tool capable of: (i) provide a rapid and reliable diagnostic aid, (ii) standardize image interpretation, and (iii) offer recommendations based on integrated clinical analyses, such as risk or complication prediction. This approach could improve the diagnosis and personalized management of RDS.