Soybeans are widely grown crops that have numerous uses, including as a food source, animal feed, and biofuel, as well as for the production of various chemicals. They are a rich source of plant-based protein and are also high in fiber, vitamins, and minerals. Due to their nutritional value and health benefits, there is an increasing concern on breeding soybeans with improved protein, fatty acid and isoflavone content. Soybeans are currently one of the primary dietary sources of isoflavones; these phytoestrogens have numerous health benefits, particularly for women's health, being increasingly used in the production of dietary supplements in the last decade. Isoflavones have been shown to have positive effects on human health, such as: alleviating the menopausal symptoms, reducing the risk of certain types of cancer (breast, prostate, and colon cancer), lowering the cholesterol levels, improving heart health by decreasing inflammation and increasing the blood flow, protective effect against osteoporosis, reducing the risk of depression and anxiety, even a positive effect on cognitive function and mental health. In this context, the goal of this research is to provide a combined approach of high performance liquid chromatography (HPLC) and chemometric techniques, able to highlight in a fast and convenient way the isoflavones’ content of soybean seeds belonging to different genotypes. A fast and sensitive HPLC method have been developed, optimized and validated for the analysis of the target analytes: isoflavone analysis was accomplished using a Flexar UHPLC system with UV detection, enabling the separation of genistein, glycitein, daidzein, daidzin, glycitin and genistin in less than 9 minutes. The resulted chromatographic data were further preprocessed (autoscalled), then subjected to principal component analysis (PCA) using Matlab. In this study, soybean seeds originating from genotypes harvested at the Research & Development Station for Agriculture, Turda - Romania were used. The analyzed genotypes showed particular isoflavones profiles, depending on genetic factors, the major isoflavones being the glycosides daidzin and genistin (more than 100 mg/ 100 g). The resulted PCA model revealed both the genotypes with the best quality attributes and similarities between the studied ones. Overall, the proposed approach can be considered not only for quality control assessment purposes, but also for assisting breeding programs targeted to develop new genotypes with the desired isoflavones’ content.