This paper analyses the relationship between translational technology and learning outcomes and investigates the type of translational technology most beneficial towards students' translations of legal texts. This study tests whether differences were found in the learning outcomes of legal text translation for students with high and low placement test scores using Machine Learning. Translations were conducted from Indonesian to English and vice versa, encompassing students from leading Indonesian universities enrolled in a professional legal translation certification programme. This research was designed with a treatment by level 3x2, quantitatively analysing the impacts of Machine Learning, Google Translate, and Online Dictionaries. The study revealed statistically significant interactive effects among the variables of translational technology in relation to the outcomes of legal translation learning. The data indicated variances in the students' learning with Machine Learning demonstrating the most substantial influence. We also found that low-scoring students on the placement test who used Machine Learning in translating legal texts revealed better learning outcomes than high-scoring students. This insight is useful for educators and scholars designing legal translation courses. This could also serve as a foundational element in the field of English for Specific Purposes particularly concerning the integration of technology in legal translation education. [Note: The page range (568-593) shown on the PDF is incorrect. The correct page range is 568-594.]