The determination of crude oil assay is a lengthy, tedious, and costly process. The conventional approach to perform an assay consists of a limited set of measurements on the crude oil and its fractions. Most often, only a few boiling points, densities, and other property measurements are available for selected distilled fractions or the whole crude. Thus, it is necessary for crude oil assay experts to predict or estimate missing properties to meet various business needs, e.g., refinery planning and scheduling and refinery process simulation. Lower order polynomial expressions are used for interpolation and arithmetic probability scale is used for extrapolation of boiling point curves. Statistically derived predictive methods are also extensively used in the industry for the prediction or estimation of crude oil assays. Analytical methods may predict crude oil properties by correlating the data obtained with rapid surrogate measurements (usually spectroscopic) to those of reference crude assays. The key elements of this molecular based assay characterization approach are presented. This is an abstract of a paper presented at the 2013 AIChE Spring Meeting & 9th Global Congress on Process Safety (San Antonio, TX 4/28-5/2/2013).