Sesame (Sesamum indicum L.) is an oilseed crop with great significance due to its nutritional, industrial and economical values. However, farmers still produce sesame cultivars with low yielding performance and other undesirable characteristics like seed shattering. Assessment on availability of genetic diversity and information on association of traits are the prerequisites to meet crop improvement goals in sesame. The experiment was conducted at Pawe Agricultural Research Center during 2019 main cropping season. The experiment was consisted 64 sesame genotypes; and the experiment was laid out on 8x8 simple lattice design. Data were recorded on 36 traits (11 qualitative and 26 quantitative) of sesame. Statistical analyses were computed using R and SAS University Edition 9.4. Summary statistics on qualitative traits and ANOVA on quantitative traits revealed the presence of genetic variability among sesame genotypes. High H2bs (>50%) coupled with high GA% (>20%) were recorded on plant height to first branch, capsule length, number of primary branches/plant, number of branches/plant, number of capsules on main stem/plant and number of capsules/plant. Correlation analysis indicated that seed yield/plant had highly significant phenotypic and genotypic correlation with plant height (0.60, 0.60), length of capsule bearing zone (0.77, 0.79), number of primary branches/plant (0.66, 0.70), number of branches/plant (0.67, 0.69), number of capsule on main stem/plant (0.80, 0.82), number of capsules/plant (0.90, 0.91), number of seeds/capsule (0.28, 0.32), oil content (0.24, 0.33) and bacterial blight disease severity (-0.60, -0.75). Path coefficient analysis showed seed yield was directly and considerably affected by number of primary branches/plant (0.94), number of capsules on main stem/plant (0.47) and number of secondary branches/plant (0.33) whereas other seed yield related traits considerably affect it indirectly. Shannon Weiner diversity index and cluster analysis revealed the presence of genetic diversity in sesame. The most determinant traits which accounted higher loadings on PC1 and FA1 were bacterial blight disease severity, plant height, length of capsule bearing zone, number of primary branches/plant, number of capsules on main stem/plant, number of capsules/plant and seed yield/plant. The present study indicated the presence of genetic potential to be exploited in improvement of seed yield and seed quality through selection and combining desirable traits. Keywords: - Correlation, cluster analysis, factor analysis, genetic variability, heritability, path coefficient, principal component analysis