The study assessed the molecular and morphometric diversity of 96 aromatic short-grain rice (Oryza sativa L.) genotypes. Based on 27 polymorphic SSR markers, the genotypes were grouped into 6 clusters with 18, 22, 10, 13, 14, and 19 genotypes, respectively. The number of detected alleles ranged from 2 to 5 with a mean of 3 alleles per locus. The number of effective alleles per locus was 2.38 which varied from 1.07 to 3. Shanon information index varied from 0.15 to 1.37 with an average of 0.90. The expected heterozygosity varied from 0.07 to 0.72 with an average of 0.54, while the gene diversity varied from 0.07 to 0.71 with an average of 0.54. PIC value varied from 0.23 to 0.85 with an average of 0.66. The model-based genetic population structure detected a sharp peak of Delta K detected at K = 4 and the entire populations were grouped into four sub-populations. The highest genetic distance was observed between populations 3 and 4 (0.3886) and the least between populations 1 and 4 (0.2900). The principal coordinated analysis (PCoA) explained about 27.92% of the total variations by the first two coordinates. The AMOVA revealed a 20% variation among the population and an 80% variation within the population. The average inbreeding coefficient of subpopulations relative to the total population (FST) detected was high (0.22) with a range of 0.065 to 0.440. The mean gene flow (Nm) was also high (1.45) which varied from 0.318 to 3.580 in individual SSR loci. The phenotypic diversity analysis grouped the entire 96 genotypes into 4 major clusters. Grain length varied from 4.6 to 5.086 mm with a mean of 4.87 mm. Grain length elongation after cooking ranged from 2.39 to 2.63 with an average of 2.49. Amylose content varied from 1.92 to 2.072% with an average of 1.97%. The mean alkaline spreading value varied from 4.29 to 4.43 with a mean of 4.35. Gel consistency varied from 2.5 to 23.84 with an average of 22.9. Grain yield per plant ranged from 5.10 to 21.50 g with an average of 12.08 g. Based on grain yield per plant, Dubraj, Chhabiswa, and Gatia were identified as the most promising. Principal component analysis (PCA) extracted 4 PCs explaining about 71.69% of the total variance wherein the first two PCs accounted for 50.44% of the total variations. The high allelic and genetic diversity information in the present study would be useful for the selection of donors in a breeding program.