Soybean (Glycine max (L.) Merr.) is an economically important crop worldwide including Ethiopia. In Ethiopia, considerable genetic materials are available. However, research on soybean genetic variability and association of traits in the study area was limited. Hence, a field experiment was conducted to estimate genetic variability and trait associations of 81 soybean genotypes at Metema and West Armachiho, West Gondar, Ethiopia. The trial was laid out in a 9 x 9 simple lattice design in 2020 main cropping season. Data were taken on both quantitative and qualitative traits. Data analyses were done using SAS, Minitab, and Past Software for analysis of variance, cluster, path, and principal component analyses. Combined analysis of variance revealed highly significant (p<0.01) differences among genotypes for the studied traits, implying existence of variability. Genotype x location interactions were also significant (p<0.05) for most of the traits. Estimated Shannon diversity index indicates polymorphic variation for most of the traits. The phenotypic coefficient of variation ranged from 4.63%-37.76% for protein content and seed yield, while the genotypic coefficient of variation varied from 1.24% -34.58% for pod length and seed yield, respectively. Broad sense heritability values ranged from 4.03% for pod length to 94.84% for days to 50% flowering. Genetic advance as percent of mean was varied from 0.51%-65.22% for pod length and seed yield, respectively. High heritability coupled with high genetic advance was observed for number of pods per plant, and seed yield indicating possibility for improving these traits through selection. Seed yield exhibited positive and significant correlations with most studied both at phenotypic and genotypic levels. Path coefficient analysis indicated days to maturity and harvest index showed highest phenotypic and genotypic positive direct effects, respectively on seed yield. The cluster analysis grouped the 81 genotypes into six clusters based on quantitative traits, and cluster I was found to be the largest (63% of genotypes) cluster. The highest inter-cluster distance was noted between cluster II and VI (D2=154.64), which would indicate, genotypes of these clusters are divergent and can be exploited in breeding for hybridization program. Principal component analysis revealed that 77.98% of the total variation among genotypes was explained by the first four components. Generally, the present study indicated existence of reasonable variability among genotypes, and this variability shall be exploited for future soybean improvement program.