In this study, the Near-infrared (NIR) and Ultra-violet visible (UV-Vis) spectroscopy methods, which are frequently used in pharmaceutical industry, were applied to the environments where Paracetamol, Propyphenazone and Caffeine active substances are present, and the spectroscopic data obtained were evaluated comparatively with Independent Component Analysis - Artificial Neural Network (ICA-ANN) and Partial Least Squares-1 (PLS-1), which are powerful chemometric methods. When using solid agents in NIR method, liquid solutions equivalent to them were used in UV-Vis method. Following the application of both methods, spectral data were evaluated as chemometrics and in both spectroscopic methods ICA-ANN method yielded more accurate results than PLS-1. High recovery rates and relatively low standard deviations were found in the applied methods and recommended for use in the pharmaceutical industry.