This study developed a deep-learning framework using magnetic resonance fingerprinting (MRF) to detect focal cortical dysplasia (FCD), a common cause of drug-resistant epilepsy, across the whole brain. By combining MRF-derived T1, T2, tissue fraction, and morphometric maps, the model achieved 80% sensitivity with fewer false positives than models using standard clinical MRI. These results highlight MRF’s potential as a powerful, single-scan tool for improving FCD detection.