Simplifying text while preserving its meaning is a complex yet essential task, especially in sensitive domain applications like legal texts.When applied to a specialized field, like the legal domain, preservation differs significantly from its role in regular texts.This paper introduces FrJUDGE, a new dataset to assess legal meaning preservation between two legal texts.It also introduces JUDGEBERT, a novel evaluation metric designed to assess legal meaning preservation in French legal text simplification.JUDGEBERT demonstrates a superior correlation with human judgment compared to existing metrics.It also passes two crucial sanity checks, while other metrics did not: For two identical sentences, it always returns a score of 100%; on the other hand, it returns 0% for two unrelated sentences.Our findings highlight its potential to transform legal NLP applications, ensuring accuracy and accessibility for text simplification for legal practitioners and lay users.Annotators.We selected five native Frenchspeaking law students at the Faculty of Law of University Laval as our annotators.A meeting was held with them to introduce the task, instructions, and annotation guide and interface.Instructions included that they must spend at most 5 minutes per sentence pair.Furthermore, 15 instances were annotated during a pilot phase to familiarize them with the task.Finally, during a second meeting after evaluating the practice instance, annotators received feedback and advice on what phenomena