We report comparison and assessment of the clinical utility of different automated methods for the estimation of the alpha frequency in electroencephalograph (EEG) and compare them with visual evaluation. A total of 56 consecutive patients, aged 17 to 78 years, who had a routine EEG recording, were included, and they were grouped as patients with epilepsy (Ep) and without epilepsy (nEp). Five different methods were used for alpha frequency estimation: visually guided manual counting and visually guided Fourier transform, and 3 methods were fully automated: time domain estimation of alpha (automatic assessment of alpha waves in time domain [ATD]) and 2 fast Fourier transform (FFT)-based methods, a segmented (automatic assessment of EEG segments by FFT) and one full FFT (automatic assessment of whole EEG by one FFT of the full recording [AWF]). The AWF discriminated significantly between Ep and nEp. Visually guided manual counting showed an almost significant difference independently in the 2 occipital electrodes. The ATD underestimated high frequencies and returned a too low mean frequency. This study shows that AWF is the best suited method for automatic assessment of the alpha frequency.