Virtual electrophoresis in proteomics can be used to search localization of proteins and their proteoforms (especially those existing in low concentrations), to identify proteoforms found in experiments etc. Although the problem of predicting the isoelectric point is well studied, the need of electrophoretic shift correction is usually ignored. Researchers simply use the brutto molecular weight of the protein. In this study four data sets taken from the literature sources and the SWISS-2DPAGE database have been used to build correction equations for prediction of the electrophoretic shift (123, 72, 118 and 470 points, respectively). Two groups of models were built. The first model was based on the amino acid composition of proteins, the second one, on analysis of parameters calculated by amino acid sequences (theoretical molecular weight, hydrophobicity, charge distribution, ability to form helix structures). The coefficient of determination ranged from 0.35 to 0.75 in each single set, but cross-prediction between samples did not gave satisfactory results. At the same time, the direction of correction was predicted correctly in 74% of cases. After combining of the samples and dividing pooled data into 2 representative sets, the coefficient of determination during in the process of learning ranged from 0.44 to 0.51, and R2 of predictions were not less than 0.39. The direction of correction was predicted correctly in 80% of cases. This prediction models have been integrated into the program pIPredict v.2, freely available at http://www.ibmc.msk.ru/LPCIT/pIPredict.