Proteomics requires a large-scale, simultaneous separation of proteins from a mixture, assessment of the relative abundance of these molecules, and identification and characterization of each component. In 2-D PAGE separations, the best method of choice for protein analysis, separation of all the proteins present in the sample is still far to be achieved and comigrating proteins in the same spot are in general present. A statistical estimation of the degree of spot overlapping present in a 2-D PAGE separation is here described: for different conditions of spot overcrowding in the map, the degree of overlapping can be quantified in terms of purity degree of each spot or percentage of proteins that will appear in the map as a single spot. A computer simulation approach is described: it is based on the protein separation pattern present in the experimental maps. The results thus obtained are compared to a theoretical model (statistical degree of peak overlapping model) based on random spot position. The described procedures were applied to an experimental reference map of human plasma. The severity of spot overlapping in 2-D PAGE maps is estimated and the influence of different experimental conditions (strip dimension, detector system performance, p/ range) is discussed. These informations are useful to quantitatively estimate the degree of error associated with identification and quantitation of each protein and to set-up experimental conditions which will increase resolution and greatly decrease the probability of spot overlapping.