Respiratory Syncytial Virus (RSV) poses a substantial threat to infants, often leading to challenges in hospital capacity. With recent pharmaceutical developments to be used during the prenatal and perinatal periods aimed at decreasing the RSV burden, there is a pressing need to identify infants at risk of severe disease. Using machine learning techniques, the aim is to stratify the risk of developing clinically severe RSV infection in infants under one year of age.