The discovery of viable biomarkers or indicators of disease states is complicated by the inherent complexity of the chosen biological specimen. Every sample, whether it is serum, plasma, urine, tissue, cells, or a host of others, contains thousands of large and small components, each interacting in multiple ways. The need to concentrate on a group of these components to narrow the focus on a potential biomarker candidate becomes, out of necessity, a priority, especially in the search for immune-related low molecular weight serum biomarkers. One such method in the field of proteomics is to divide the sample proteome into groups based on the size of the protein, analyze each group, and mine the data for statistically significant items. This chapter details a portion of this method, concentrating on a method for fractionating and analyzing the low molecular weight proteome of human serum.