  In this work, I discuss how Large Language Models can be applied in the legal
domain, circumventing their current drawbacks. Despite their large success and
acceptance, their lack of explainability hinders legal experts to trust in
their output, and this happens rightfully so. However, in this paper, I argue
in favor of a new view, Justifiable Artificial Intelligence, instead of
focusing on Explainable Artificial Intelligence. I discuss in this paper how
gaining evidence for and against a Large Language Model's output may make their
generated texts more trustworthy - or hold them accountable for misinformation.
