Sesame (Sesamum indicum L.) breeding requires simultaneous improvement of yield, phenology, plant architecture, seed attributes and quality traits, however, correlations among traits can complicate direct selection. The present study evaluated 45 sesame genotypes for 14 agronomic and quality-related traits using principal component analysis (PCA), factor analysis and the multi-trait genotype–ideotype distance index (MGIDI). Five principal components had eigenvalues greater than one and collectively accounted for 69.02% of the total variation. PC1, PC2, PC3, PC4 and PC5 explained 24.52, 18.45, 9.65, 8.70 and 7.71% of the variation, respectively. The retained factor solution grouped the traits into five interpretable dimensions. FA1 was primarily associated with number of capsules per plant, SCMR, seed yield per plant and harvest index, FA2 with plant height, first capsule height, days to maturity and specific leaf area, FA3 with primary and secondary branching, FA4 with oil content and days to 50% flowering, and FA5 with thousand-seed weight and capsule length. The MGIDI values ranged from 2.754 to 6.552, with G30, G33, G35, G43, G17, G8 and G39 occupying the first seven positions. At a 15% selection intensity, these seven entries would be retained according to the supplied MGIDI ranking. The largest reported selection differentials and expected gains occurred for number of capsules per plant and seed yield per plant, with selection differential percentages of 32.52 and 32.28%, respectively. The combined PCA–factor analysis–MGIDI framework reduced the dimensionality of the 14-trait dataset and provided an integrated criterion for multi-trait genotype prioritization. The conclusions are conditional on the supplied ideotype directions and derived statistical outputs, the original experimental design, location, season, replication and raw genotype × trait data should be verified before submission.