The identification, characterization and quantification of crystal forms are becoming increasingly important within the pharmaceutical industry. A combination of different physical analytical techniques is usually necessary for this task. In this work solid-state techniques, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and X-ray powder diffractometry (XRPD) were combined to analyze polymorphic purity of crystalline ranitidine-HCl, an antiulcer drug, H2 receptor antagonists. A series of 12 different mixtures of Form 1 and 2 was prepared by geometric mixing and their DRIFT spectra and XRD powder patterns were obtained and analyzed, either alone or combined together, using Artificial Neural Networks (ANNs). A standard feed-forward network, with back-propagation rule and with multi layer perceptron architecture (MPL) was chosen. A working range of 1.0-100% (w/w) of crystal Form 2 in Form 1 was established with a minimum quantifiable level (MQL) of 5.2% and limit of detection of 1.5% (w/w). The results demonstrate that DRIFTS combined with XRPD may be successfully used to distinguish between the ranitidine-HCl polymorphs and to quantify the composition of binary mixtures of the two.