Statistical Shape Model (SSM) for infant cranial analysis is challenging due to open sutures, which complicate the process of establishing anatomical correspondences between models. This study proposes a Wrap4D-based methodology for accurate preparation of newborn’s cranial samples used in SSM. The approach integrates skin and skull segmentation with a guided wrapping technique that supports suture filling through anatomically-guided surface adaptation, while ensuring high fidelity in shape alignment. SSM algorithm uses the prepared dataset of 75 normal infant skulls from Meyer Children’s Hospital IRCCS for the creation of a template, which serves as the reference model for defining a standard newborn’s cranial shape. The methodology offers a rapid, reproducible and anatomically accurate solution for modelling suture closure. Preliminary results led to a Generalization of 1.245 mm, a Specificity of 2.659 mm and a Compactness of 98% with 20 modes of variation. Finally, quantitative comparison with traditional wrapping techniques reveals Wrap4D superior anatomical preservation in the region of suture.