Digital and computational methods are an essential part of palaeography and codicology, as they are for Medieval Studies in general. In terms of computational approaches, computer vision and artificial intelligence (machine learning) are applied to historical material, for instance in the automatic transcription of manuscripts (Handwritten Text Recognition), as well as in research towards methods for automatically distinguishing or identifying scribes or scripts, or dating and localising manuscripts. Digital tools also enable researchers to visualise, interact with, and communicate in new ways, and these are also important to palaeography and codicology. Achieving this requires a shared mental (conceptual) and digital model, and so digital approaches have led to renewed discussion about shared vocabularies, but they have also pushed palaeographers and codicologists to new levels of precision in their terminology and in their descriptions of handwriting, codicological structures and other aspects of medieval books and charters. This in turn allows the aggregation of images and data from different libraries and archives around the world, improving access to images and information. At the same time, these methods are also helping palaeographers and codicologists to think about their material in new ways.