In this paper the theoretical framework used to build a superfamily probability in electron microscopy (SPI-EM) is presented. SPI-EM is a new tool for determining the homologous superfamily to which a protein domain belongs looking at its three-dimensional electron microscopy map. The homologous superfamily is assigned according to the domain-architecture database CATH. Our method follows a probabilistic approach applied to the results of fitting protein domains into maps of proteins and the computation of local cross-correlation coefficient measures. The method has been tested and its usefulness proven with isolated domains at a resolution of 8 A and 12 A. Results obtained with simulated and experimental data at 10 A suggest that it is also feasible to detect the correct superfamily of the domains when dealing with electron microscopy maps containing multi-domain proteins. The inherent difficulties and limitations that multi-domain proteins impose are discussed. Our procedure is complementary to other techniques existing in the field to detect structural elements in electron microscopy maps like alpha-helices and beta-sheets. Based on the proposed methodology, a database of relevant distributions is being built to serve the community.