Chromatography is a technique for separating the chemical components of a mixture, and a chromatogram is used to identify the components based on retention time. Usually, peak identification is based on retention time, which is not ideal alone since retention time is prone to shifts. Additional detectors, such as, Mass spectrometers are commonly used to assist, but are a very expensive option. For analytes having nearly the same retention times, peak shape-based identification yields a correct prediction. Peak shape is a characteristic signature of the identity of an analyte, so there is a unique normalized peak shape for each analyte. Given the data, normalized peak shapes are obtained, and can be compared with unknown analytes to determine if analytes match and the goodness of the match. The significance of a match can be judged by several methods, such as, R2 values and absolute percent error. This project explores another method using the Kolmogorov-Smirnov (K-S) test and probability distributions.