Legal knowledge engineering methodology for epistemologically sound, large scale legal expert systems is developed in this dissertation. A specific meta-epistemological method is posed for the transformation of legal domain epistemology to large scale legal expert systems; the method has five stages: 1. domain epistemology; 2. computational domain epistemology; 3. shell epistemology; 4. programming epistemology; and 5. application epistemology and ontology. The nature of legal epistemology is defined in terms of a deep model that divides the information of the ontology of legal possibilities into the three sorts of logic premises, namely, (1) rules of law for extended deduction, (2) material facts of cases for induction that establishes rule antecedents, and (3) reasons for rules, including justifications, explanations or criticisms of rules, for abduction. Extended deduction is distinguished for automation, and provides a map for locating, relatively, associated induction and abduction. Added to this is a communication system that involves issues of cognition and justice in the legal system. The Appendix sets out a sample of draft rule maps of the United Nations Convention on Contracts for the International Sale of Goods, known as the Vienna Convention, to illustrate that the substantive epistemology of the international law can be mapped to the generic epistemology of the shell. This thesis deflects the ontological solution back to the earlier rule-based, case-based and logic advances, with a definition of artificial legal intelligence that rests on legal epistemology; added to the definition is a transparent communication system of a user interface, including an interactive visualisation of rule maps, and the heuristics that process input and produce output to give effect to the legal intelligence of an application. The additions include an epistemological use of the ontology of legal possibilities to complete legal logic, for the purposes of processing specific legal applications. While the specific meta-epistemological methodology distinguishes domain epistemology from the epistemologies of artificial legal intelligence, namely computational domain epistemology, program design epistemology, programming epistemology and application epistemology, the prototypes illustrate the use of those distinctions, and the synthesis effected by that use. The thesis develops the Jurisprudence of Legal Knowledge Engineering by an artificial metaphysics. / Doctor of Philosophy (Ph.D)