The linguistic nature of Qumran Hebrew (QH) remains a central debate in the study of the Dead Sea Scrolls (DSS). Although some schol-ars view QH as an artificial imitation of Biblical Hebrew (BH), others argue that it represents a spoken dialect of ancient Judea. The present study employs computational lin-guistic techniques, clustering, classification, and machine learning, to analyze the relation-ship of QH with Biblical and Mishnaic He-brew. Preliminary findings confirm existing scholarly conclusions regarding the linguistic affinity of certain texts. This demonstrates that our methodology has a fundamental capacity to identify linguistic relationships. They also contribute new leads, on which we are now working to refine and enhance our analytical methods so as to provide founded insights into the historical development of Hebrew and the process of DSS textual composition.