This article presents the digital edition of Robert Musil’s work (Klagenfurter Ausgabe) and its role in a digital humanities project aimed at reconstructing Musil’s activity in the WWI journal Tiroler Soldaten-Zeitung. First, the article reviews the ways in which the computational methods of stylometry are applied to attribute the anonymous texts published in the Klagenfurter Ausgabe. Second, it explores how optical character recognition (OCR) software is employed to expand the corpus. At the core of this methodology two machine learning algorithms are trained and revised using the transcriptions of the Klagenfurter Ausgabe, to reach an accuracy of about 99.9% in the digitization of the Tiroler Soldaten-Zeitung texts. The work of this project offers not only the possibility of expanding stylometric analysis to the whole journal, but also of improving the transcriptions of the Klagenfurter Ausgabe.