Background: Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) is usually associated with a poor response to antiseizure medications. We focused on MTLE-HS patients who were seizure free on medication to: (1) determine the clinical factors associated with seizure freedom and (2) develop a machine-learning classifier to better earlier identify those patients. Methods: We performed a retrospective, multicentric study comparing 64 medically treated seizure-free MTLE-HS patients with 200 surgically treated drug-resistant MTLE-HS patients. First, we collected medical history and seizure semiology data. Then, we developed a machine-learning classifier based on clinical data. Results: Medically treated seizure-free MTLE-HS patients were seizure-free for at least 2 years, and for a median time of 7 years at last follow-up. Compared to drug-resistant MTLE-HS patients, they exhibited: an older age at epilepsy onset (22.5 vs 8.0 years, p < 0.001), a lesser rate of: febrile seizures (39.0% vs 57.5%, p = 0.035), focal aware seizures (previously referred to as aura)(56.7% vs 90.0%, p < 0.001), autonomic focal aware seizures in presence of focal aware seizure (17.6% vs 59.4%, p < 0.001), dystonic posturing of the limbs (9.8% vs 47.0%, p < 0.001), gestural (27.4% vs 94.0%, p < 0.001), oro-alimentary (32.3% vs 75.5%, p < 0.001) or verbal automatisms (12.9% vs 36.0%, p = 0.001). The classifier had a positive predictive value of 0.889, a sensitivity of 0.727, a specificity of 0.962, a negative predictive value of 0.893. Conclusions: Medically treated seizure-free MTLE-HS patients exhibit a distinct clinical profile. A classifier built with readily available clinical data can identify them accurately with excellent positive predictive value. This may help to individualize the management of MTLE-HS patients according to their expected pharmacosensitivity.