This study explores advanced Electroencephalogram (EEG)-based methods for epileptic seizure detection, utilizing preprocessing and diverse feature extraction techniques. Employing machine learning algorithms like Random Forest, it achieves promising accuracy, offering valuable insights for timely intervention and personalized treatment in epilepsy management, contributing to enhanced diagnostic tools.