Sugar beet is an important agricultural crop product that has been produced and consumed worldwide since the eighteenth century and can adapt to various climatic and soil conditions. The two fundamental building blocks of any crop improvement program are germplasm resources, which contain genetic diversity and phenotypic expression of desired traits. In this study, a total of 58 sugar beet genotypes including 12 from Turkey, 4 from India, 12 from the United States of America, 16 from Iran, 12 from England and Beta vulgaris L. subsp. maritima L. Arcang. as wild species were characterized using 15 inter-primer binding site (iPBS) markers that produced intense and polymorphic bands in the germplasm library. Using these 15 iPBS markers, 102 polymorphic bands were produced and the average number of polymorphic bands was determined as 6.8. Polymorphism information content (PIC) values ranged between 0.58 and 0.83, and the average PIC value was found to be 0.70. It was determined that the most genetically different genotypes were PI 590697-US11 and PI 171508-TR8, with a distance of 0.73. Clustering algorithms Unweighted Pair Group Method Algorithm (UPGMA) and Principal Coordinate Algorithm (PCoA) confirmed that genotypes are an important factor in clustering, and STRUCTURE analysis divided sugar beet gene resources into six populations. Also, the analysis of molecular variance (AMOVA) showed that there was 8% variance among populations and 92% variance within populations. This is the first study to investigate the genetic diversity and population structure of sugar beet germplasm using the iPBS-retrotransposon marker system. The results of this research emphasized that iPBS markers are very successful and effective in examining the genetic diversity of sugar beet germplasm. The results obtained in this study provide a theoretical basis for future selection and breeding of superior sugar beet germplasm sources.