목적: Idiopathic sudden sensorineural hearing loss (ISSHL) is an otologic emergency. An early prediction of prognosis may facilitate proper treatment. Therefore, we investigated its prognostic factors for predicting a recovery in patients with ISSHL using machine learning models 방법:We retrospectively reviewed the medical records of 433 patients with ISSHL who were treated at a tertiary medical institution between January 2015 and September 2020. A total of 52 variables were analyzed to predict hearing recovery. Recovery was defined using Siegel’s criteria, and the patients were categorized into recovery and non-recovery groups. Recovery was predicted by various machine learning models. In addition, the prognostic factors were analyzed using the difference in the loss function. 결과:The comparison of recovery and non-recovery groups revealed significant differences in variables, including age, hypertension, history of cardiac disease and previous hearing loss, ear fullness, dizziness, duration of hospital admission, delay between symptom onset and treatment, initial hearing level of the affected and unaffected ears, post-treatment hearing level, and treatment methods. The deep neural network (DNN) model showed the highest predictive performance. (accuracy: 89.66%, area under the receiver operating characteristic curve: 0.9646) As a result of analyzing the prognostic, it was confirmed that the history of hypertension and previous hearing loss and dizziness were important in predicting the prognosis. 결론:The DNN model showed the highest predictive performance for recovery in patients with ISSHL. The factors with prognostic value were also identified. Further studies using a larger patient population are warranted.