High conversion copolymers may experience a strong variation in composition as a function of monomer conversion, and since the compositional heterogeneity of copolymers varies as the size of the chains grows, this poses a problem in determining the bivariate distribution of masses and composition in copolymers. Although several methods have been proposed to determine bivariate distributions, relatively little data are available on this important aspect of copolymer characterization, perhaps because of the complexity of the methods available up to the present time. We propose here a generally applicable method to determine bivariate distribution of masses and composition in copolymers. SEC fractionation of two random copolymers, poly(methyl methacrylate)/polybutyl acrylate (PMMA/PBA) obtained at high and low conversions, respectively, was used to collect nearly monodisperse fractions that allowed the computation of the corresponding molar masses (by matrix-assisted laser desorption ionization mass spectrometry, MALDI, measurements) and of compositions (by NMR measurements) for the two copolymers. Bivariate distribution maps were derived by combining SEC/NMR and SEC/MALDI data with Stockmayer＇s theoretical distribution to estimate the composition distribution of each fraction.