The success of good breeding program usually depends upon the genetic variability present in the breeding materials, however, spatial and temporal studying on the amount, kind and magnitude of variability as well as genetic relationship of traits are not efficiently exploited yet. The present investigation was designed to assess the extent of variability, genetic advance, heritability and interrelation of different traits of 100 chickpea genotypes using triple lattice design in Takusa district, North Gondar, Ethiopia, during 2018/19 main cropping season. The data were recorded on days to 50 percent flowering, days to physiological maturity, seed filling period, plant height (cm), number of primary branches per plant, number of secondary branches per plant, number of pods per plant, number of seeds per pod, 100 seed weight (g), above ground biomass (kgha-1), harvest index, grain yield (kgha-1) and protein content (%). The examined genotypes were highly significant for all studied traits. The magnitude of genotypic and phenotypic coefficient of variation indicated the presence of variability among advanced lines. The trait above ground biomass exhibited the highest range of variability followed by grain yield, number of pods per plant, hundred seed weight, days to flowering and days to maturity. The highest estimates of genotypic and phenotypic coefficient of variation were exhibited grain yield followed by number of pods per plant, number of secondary branches per plant, above ground biomass, and harvest index. The highest broad sense heritability coupled with high genetic advance were observed for grain yield, number of pods per plant, number of secondary branches per plant, above ground biomass and hundred seed weight. In the present investigation inter distance (D2) values were ranged from 81.6 to 874.5 with a total of 9 significant clusters. The first four principal components, whose Eigenvalues greater than one, accounted more than 81.5% of the total variation. Generally the existence of huge variability infers no more need induced variation, Exploiting the existing variation is enough to improve chickpea grain yield only thorough simple selection by giving due attention for above ground biomass, number of secondary branch per plant, number of pod per plant and harvest index. Keywords: Characters, Clustering, Chickpea, Genetic variability, Genotype