Methods that predict antibody epitopes could help to promote the development of diagnostic tools, vaccines or immunotherapies by affecting the epitope binding of antibodies during an immunological response to antigens. It is generally assumed that there is a direct relationship between antibody accessibility to antigens and accessible surface of proteins. Based on this assumption, prediction systems often includes solvent accessibility values calculated from the primary sequence of proteins or from their three dimensional structures as a predictive criterion. However, the current prediction systems seem weakly efficient in view of benchmark tests. We were interested in evaluating how amino acids that have been experimentally identified as epitopic elements could differ from the rest of the antigenic molecule at the level of surface exposure, hence we assessed the average accessibility of epitopes. The approach used here utilises published epitopes deduced from numerous identification techniques, including sequence scanning and structure visualisation after crystallography, and it involves many types of antigens from toxins to allergens. Our results show that epitopic residues are not distributed among any specific Relative Surface Accessibility and Protrusion Index values and that, in some cases, epitopes cover the entire antigenic sequence.These results led to the conclusion that the classification of known epitopes with respect to the experimental conditions used to identify them should be introduced before attempting to characterise epitopic areas in a generic way