The presently accepted theory for gradient separations of small molecules has been used to develop a predictive model for peptides and proteins as samples, using reversed-phase high-performance liquid chromatography. Given the experimental conditions (gradient time, flow-rate, temperature, etc.), the molecular weight of the sample, and certain column characteristics (Knox parameters, column dimensions, particle diameter, etc.), it is possible to calculate the overall results of a given separation by gradient elution: peak capacity or average resolution, peak volume or relative peak height, etc. This information can in turn facilitate the optimized separation of any sample. The present model assumes that isocratic and gradient retention are interrelated for peptide molecules, in the same fashion as for small molecules. This assumption has been verified for various peptides and proteins and further used to gain new insight into the control of retention and band-spacing in gradient elution.