Cranioplasty has a long history in the field of virtual surgical planning (VSP), and cranial reconstruction has always been at the center of great interest in the application of innovative technologies. This chapter explores in detail the digital protocol for the neurosurgical reconstruction of skull defects. A classification subdivides cranial defects into small entities, for which a context-driven reconstruction based on spline methods is generally effective; large defects, for which generative methods are advised, like statistical shape modeling, closest donor template, or deep learning. Moreover, combined cranio-orbital defects are of great relevance given their esthetical implications in maxillofacial surgery, and reconstruction needs to be tailored to replicate, when possible, the contralateral integer anatomy. Last, emphasis is given in design techniques that enable to perform in-house cranial reconstruction through intraoperative polymethyl metacrylate modeling using combinations of 3D printed molds, which represent a versatile and effective method to reconstruct craniofacial defects.