For decades, local and traditional species have been neglected and replaced by industrial and improved species. Sweet chestnut ‘Castanea sativa MILL.’, found in a small area in northern Morocco, is no exception. Indeed, Moroccan ecotypes are neither classified nor characterized. This study aims to evaluate the local genetic resources of Castanea sativa MILL. via multivariate analysis of morphometric parameters of leaves. The study involved 6200 leaves from 31 villages in 3 regions; 10 trees/village and 20 leaves/tree were sampled. Then eight morphometric parameters were analyzed: lamina length (LL), lamina width (LW), petiole length (PL), distance from the base of the leaf to the widest point of the leaf (DBW), surface (S), perimeter (P), and ratios LL/LW and LL/DBW. Analysis of the descriptive statistics within and between ecotypes initially showed a large variation in the ten parameters studied. This finding was supported by analysis of variance (ANOVA) which revealed a very highly significant difference (p < 0.0001) for all parameters. Indeed, the analysis of agglomerative hierarchical clustering (AHC) made it possible to group the studied populations into 3 distinct groups based on the surface. Overall, the high level of variability in leaf morphometric parameters indicates that the region is an important center of genetic diversity which assessment is crucial for the implementation of conservation and enhancement strategies for this heritage.