This chapter explores alternative methods for obtaining chemical fingerprints, that being, multidimensional high-performance liquid chromatography (MDHPLC). HPLC is the most commonly used analytical separation technique for the determination of components in complex mixtures as it offers high sensitivity and can be highly selective. Sample dimensionality can be described as the number of features of the sample that can be utilized for separation purposes. Two simple examples of sample dimensionality are found for the samples of: polynuclear aromatic hydrocarbons and low-molecular-weight polymers. There are several mathematical processes that can be utilized to evaluate the orthogonality of two-dimensional (2D) systems; these include informational entropy, percentage of synentropy, peak spreading angle, and factor analysis. Depending upon the goal of the analysis, 2D separations can be carried out using either a heart-cutting process or comprehensively. The process of heart cutting involves the transport of a discrete area of interest from the first dimension to the second dimension for further separation.