Drowsiness is a leading cause of accidents on the road as it negatively affects the driver’s ability to safely operate a vehicle. This scientific research introduces a novel method to estimate driver drowsiness in real-time using EEG signals. The system monitors brain activity and translates it into an estimate of a driver's level of drowsiness, providing valuable information to prevent potential accidents. By analyzing changes in neural features, the model can effectively track drowsiness levels. This research paves the way for integrating EEG-based drowsiness detection into future driver-assistance systems.