Schwannomatosis is a rare genetic disorder characterized by the development of multiple, painful schwannomas, presenting with high variability in clinical manifestation and management complexity. To support clinical decision-making, we previously developed an Explainable Artificial Intelligence (XAI) system based on the COGNICA framework of cognitive argumentation. The system integrates the European Reference Network (ERN) GENTURIS clinical guidelines with structured, interpretable reasoning processes, enabling transparent and traceable medical recommendations. While prior work established the system’s technical feasibility, its usability and clinical acceptability among domain experts had not been systematically assessed. This study presents the results of an expert-based evaluation using a structured questionnaire that combines standardized instruments—Visual Analogue Scales (VAS), System Usability Scale (SUS), Questionnaire for User Interface Satisfaction (QUIS), User Experience Questionnaire (UEQ), and Treatment Acceptability Rating Form (TARF)—alongside open-ended feedback. Four experts from neurology, and genetics participated in the evaluation. Results demonstrate strong satisfaction and comprehension, confirming that explainable AI tools like this system can enhance medical reasoning in rare diseases. However, their effective integration into clinical workflows will require iterative refinement, clinician training, and validation in real-world settings.