Abstract: To extract the phenotypic data of leaf shape accurately, we used R language to write a package LeafShape for extracting leaf length, width, and area as well as edge digital characters by using leaf scanned image as input file. With this package, 2 496 leaf phenotypic data of 181 families were extracted in a clonal randomized block test derived from an F₁ hybrid progeny of Populus deltoides and P. simonii. Descriptive statistics, correlation analysis, and mixed linear model were applied for analyzing the phenotypic and genetic variations. In addition, clustering analysis was performed for leaf shapes according to the genetic effects of the polar radii at the leaf edge points. The findings indicated that the coefficients of variation (CV) in leaf length and width were in the range from 20% to 25% and the leaf area had the largest CV value of 42%. There were extremely significant correlations among leaf length, width, and area, with most correlation coefficients higher than 0.90. Furthermore, the phenotypic variations of the leaf length, width, and area were attributed to the genetic variation, each with a repeatability over 60% and that of 2/3 leaf area up to the highest value of 72%. Additionally, 181 clonal families were clustered into 9 groups according to the genetic effects of the polar radii at the 360 edge points. It is obvious that the 9 clusters of leaf shapes can be divided into 2 major groups, one close to the female parent P. deltoides and the other to the male parent P. simonii.