Crystal morphology is one of the key crystallographic characteristics that governs the macroscopic properties of crystalline materials. The identification of crystal faces, or face indexing, is an important technique that is used to get information regarding a crystal's morphology. However, it is mainly limited to single crystal X-ray diffraction (SCXRD) and it is often not applicable to products of routine crystallizations becasue it requires high quality single crystals in a narrow size range. To overcome the limitations of the SCXRD method, we have developed a robust and convenient Raman face indexing method based on work by Moriyama et al. This method exploits small but detectable differences in Raman spectra of crystal faces caused by different orientations of the crystallographic axis relative to the direction and polarization of the excitation laser beam. The method requires the compilation of a Raman spectral library for each compound and must be built and validated by SCXRD face indexing. Once the spectral library is available for a compound, the identity of unknown crystal faces (from any crystal that is larger than laser beam) can be inferred by collecting and comparing the Raman spectra to spectra within the library. We have optimized this approach further by developing a machine-learning algorithm that identifies crystal faces by performing a statistical comparison of the spectra in the Raman library and the Raman spectra of the unknown crystal faces. Here, we report the development of the Raman face indexing method and apply it to three different epitaxial systems: Acetaminophen (APAP) grown as an overlayer crystal on d-mannitol (MAN), d-galactose (GAL), and xylitol (XYL) substrates. For each of these epitaxial systems, the crystals were grown under various experimental conditions and have a wide range of sizes and quality. Using the Raman face indexing method, we were able to perform high-throughput indexing of a large number of crystals from different crystallization conditions, which could not be achieved using SCXRD or other analytical techniques.