Mungbean (Vignaradiata L. Wilczek) is a vital pulse crop cultivated extensively across tropical and subtropical regions, notably in Asia. Despite its nutritional and agronomic value, mungbean productivity remains low due to biotic, abiotic, and genetic constraints. This study aimed to assess genetic variability and identify key yield-contributing traits among 45 mungbean genotypes using Principal Component Analysis (PCA). The experiment was conducted during Kharif 2024 at the Research Farm of SKN College of Agriculture, Jobner, using a Randomized Block Design with three replications. Thirteen quantitative traits including yield and yield components were recorded. PCA revealed that the first four principal components had eigenvalues greater than one and together explained 72.81% of the total variation. PC1 (36.58%) was associated with seed yield, number of pods per plant, pod length, clusters per plant, and plant height—traits critical for yield improvement. PC2 (15.35%) was mainly related to phenological traits like days to flowering and maturity, while PC3 (12.56%) and PC4 (8.32%) emphasized protein content, plant height, and 100-seed weight. The PCA biplot identified genotypes such as RMG 1249-1, RMG 1196, and HUM 1 as high-performing lines, suggesting their potential use in breeding programs. Overall, PCA proved effective in simplifying trait complexity and prioritizing traits and genotypes for mungbean yield enhancement.