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The Régie du Logement du Québec (RDL) is a tribunal with exclusive jurisdiction in matters regarding rental leases. Within the framework of the ACT (Autonomy Through Cyberjustice Technologies) project, we processed an original collection of court decisions in French and performed a thorough analysis to reveal biases that may influence prediction experiments. We studied a multilabel classification task that consists in predicting the types of verdict in order to illustrate the importance of prior data analysis. Our best model, based on the FlauBERT language model, achieves F1 score micro averages of 93.7% and 84.9% in Landlord v. Tenant and Tenant v. Landlord cases respectively. However, with the support of our in-depth analysis, we emphasize that these results should be kept in perspective and that some metrics may not be suitable for evaluating systems in sensitive domains such as housing law.

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