Abstract: Computer implemented methods and systems are disclosed for obtaining predictions of legal events, such as legal and factual arguments presented to courts, juries or other adjudicative or fact-finding bodies, using machine-learning algorithms, wherein (i) unstructured data, such as natural language text from documents, such as pleadings, briefs or corpuses of evidence are converted into tokens, vectors and/or embeddings; (ii) the machine-learning algorithm(s) are provided the converted unstructured data as inputs; and (iii) the machine-learning algorithms provide confidence or probability scores predicting outcomes of legal events, such as legal proceedings or one or more legal or factual issues to be decided by particular adjudicators, tribunals or fact-finding bodies.