It is possible to classify various propolis samples based on their botanical or geographic origins, since environmental conditions and the harvest season have an impact on the chemical ingredients that make up propolis. In the current research, the determination and geographical classification of propolis samples according to their mineral/metal content are addressed. Acid digestion was employed for mineral/metal recovery and inductively-coupled plasma-optical emission spectrometry was used for accurate quantification. Multivariate techniques, PCA and PLS-DA, were applied for unsupervised and supervised classification for different propolis samples. The measured analytical data can be simply manipulated using chemometric tools, like PCA and PLS-DA. Adequate results were reported by PLS-DA to separate propolis samples that were obtained from industrial and agricultural, but not desert regions. The variations in mineral/metal contents present in propolis were helpful for discrimination purposes. Minerals, like Ca, Na, and K, were the most significant variables for propolis discrimination according to their geographical origins. Based on mineral and metal content, PLS-DA model was effective to classify propolis samples with 92% accuracy as estimated from the confusion matrix.