The aim of the present study was to propose an improved method of quantitative assessment of EEG age-related changes. 40 EEG recordings of healthy subjects (aged 0.7-78 years) were analysed. Multidimensional scaling of EEG spectral data indicated a presence of an 'age factor' related non-linearly to the chronological age. Relative integrals of FFT spectra in 6 frequency bands were utilized as predictors of age or, alternatively, logarithmized age. Three regression models based on EEG spectral indicators were examined. Regression from logarithmic predictors to logarithm of age performed best in terms of linearity and residual errors. As a result, the Brain Electric Maturation Scale was proposed, being defined by the logarithm of ratio of the age predicted from the EEG data and chronological age. The scale could serve as an objective measure of brain maturation in children, or as an age-independent indicator of slow EEG abnormalities.