This paper reports on an experiment on using case-based reasoning in Dutch administrative law. The use case is decision-support for human medical experts at the Dutch Central Office of Driving Certification who have to decide whether a citizen who applies for a driving licence is fit to drive. Case-based reasoning is investigated for this purposes because of its potential advantages over machine-learning approaches as regards transparency and explainability. Both traditional case-based reasoning, AI & Law models of precedential constraint and their combination are investigated on predictive accuracy relative to a large case base with more than 30.000 cases. A combined model is found to have the highest accuracy. The results indicate that human-in-the-loop support with a tool based on the combined model may be feasible, but whether this is indeed so requires further investigation.