Walnuts, with their health-promoting ingredients, are among the most popular nuts, and practicable methods for determining their geographical origin are needed to tackle food fraud. Authentic walnut samples (235, Juglans Regia L.) from different harvest years (2016-2019) and countries were analyzed by 1H NMR spectroscopy in combination with chemometric methods to determine their geographical origin. Two sample groups were analyzed at a time with a support vector machine algorithm to obtain two-class classifier models. In total, nine two-class models were built (e.g., Germany/China, France/Germany, and USA/Switzerland), and a repeated nested cross-validation was performed. The models obtained showed high accuracies from 78.0% (±2.3%) to 96.6% (±0.6%). Furthermore, identification of potential chemical markers in the walnut extract was performed.