This study presents a standardized boundary element method (sBEM) volume conductor model derived from averaged magnetic resonance imaging (MRI) data to improve source reconstruction accuracy in EEG. The sBEM model consists of 4770 nodes, representing the smoothed cortical envelope, skull, and skin. Electrode positions are transformed into the sBEM coordinate system using fiducials, and potential values are calculated by linear interpolation. The localization accuracy of the sBEM model is compared to simulated data and individual BEM models using epileptic spike data from 7 patients. The sBEM model shows significantly better localization accuracy, especially in basal and temporal lobe areas, compared to spherical shell models. The computational performance of the sBEM model is about 60 times slower than spherical shell models but is still reasonable for most applications. The sBEM model offers an easier and faster access to realistically shaped volume conductor models, making it a practical alternative to individualized models in clinical settings.This study presents a standardized boundary element method (sBEM) volume conductor model derived from averaged magnetic resonance imaging (MRI) data to improve source reconstruction accuracy in EEG. The sBEM model consists of 4770 nodes, representing the smoothed cortical envelope, skull, and skin. Electrode positions are transformed into the sBEM coordinate system using fiducials, and potential values are calculated by linear interpolation. The localization accuracy of the sBEM model is compared to simulated data and individual BEM models using epileptic spike data from 7 patients. The sBEM model shows significantly better localization accuracy, especially in basal and temporal lobe areas, compared to spherical shell models. The computational performance of the sBEM model is about 60 times slower than spherical shell models but is still reasonable for most applications. The sBEM model offers an easier and faster access to realistically shaped volume conductor models, making it a practical alternative to individualized models in clinical settings.