Twenty heavy and/or particle-rich crude oils have been quantitatively fractionated into saturates, aromatics, resins, and asphaltenes (SARA) by asphaltene precipitation in n-hexane and high-performance liquid chromatography (HPLC). The newly developed and fully automated HPLC method has a sample capacity corresponding to 0.6 g of heavy crude oil. The crude oils have been characterized by vibrational spectroscopy in the near-infrared (NIR) and infrared (IR) regions. Principal component analyses (PCA) of the data sets from IR and NIR were performed so that exploratory data analyses could be conducted. Partial least-squares (PLS) regression models were built for each SARA component from IR and NIR data to predict the amounts of SARA components. These models successfully fitted the experimental data from NIR analyses and showed good predictive ability for the crude oil composition. The regression models from IR data were not modeled properly for aromatics and asphaltenes but were modeled excellently for saturate and resin components. For SARA determination, NIR spectroscopy appears to be a favorable alternative to the more time-consuming fractionation method.