Forensic fiber evidence plays an important role in many criminal investigations. Nondestructive techniques that preserve the physical integrity of the fibers for further court examination are highly valuable in forensic science. Non-destructive techniques that can either discriminate between similar fibers or match a known to a questioned fiber - and still preserve the physical integrity of the fibers for further court examination - are highly valuable in forensic science. When fibers cannot be discriminated by non-destructive tests, the next reasonable step is to extract the questioned and known fibers for dye analysis with a more selective technique such as high-performance liquid chromatography (HPLC) and/or gas chromatography-mass spectrometry (GC-MS). The common denominator among chromatographic techniques is to primarily focus on the dyes used to color the fibers and do not investigate other potential discriminating components present on the fiber. Differentiating among commercial dyes with very similar chromatographic behaviors and almost identical absorption spectra and/or fragmentation patterns is a challenging task. This dissertation explores a different aspect of fiber analysis as it focuses on the total fluorescence emission of fibers. In addition to the contribution of the textile dye (or dyes) to the fluorescence spectrum of the fiber, we investigate the contribution of intrinsic fluorescence impurities – i.e. impurities imbedded into the fibers during fabrication of garments - as a reproducible source of fiber comparison. Differentiation of visually indistinguishable fibers is achieved by comparing excitation-emission matrices (EEMs) recorded from single textile fibers with the aid of a commercial spectrofluorimeter coupled to an epi-fluorescence microscope. Statistical data comparison was carried out via principal component analysis. An application of iv this statistical approach is demonstrated using challenging dyes with similarities both in twodimensional absorbance spectra and in three dimensional EEM data. High accuracy of fiber identification was observed in all the cases and no false positive identifications were observed at 99% confidence levels.