The major purpose of this study was to investigate causal relationships among the variables which are supposed to affect school achievement of elementary school children. A causal model of school achievement was formulated by the researcher on the basis of previous findings and theoretical considerations. The data for this research was collected from 303 boys and girls of sixth grade and their mothers drawn from 5 elementary schools located in Seoul. A path analysis was done to study the direct and indirect effects of the variables taken as causes on the dependent variables taken as effects. Paths whose coefficients were considered statistically not significant(e.g., p＞. 05) and/or not meaningful in terms of the size of path coefficient (e.g., less than. 07) were deleted from the causal model. Subsequent to the deletion of several paths from the model, the path coefficients in the reconstructed model were calculated and used in an attempt to reproduce the original correlation matrix. Since the discrepancies between the original and the reproduced correlations turned out to be small, it could be concluded that the data are consistant with the reconstructed model. The causal model and path coefficients .are presented in the following figure. The path diagram depicted in the figure is a recursive system. X₁ and X₂ in the model are exogenous variables and the other variables are endogenous. The general causal flow in the model is as follows: X₁ (parent’s education) and X₂ (economic status of the home) influence X₃ (psychological home environment) and X₄ (physical home environment), which in turn affect X5 (children’s self-concept) and X6 (children’s learning behaviors), which are two of the most important factors in determining X7 (children’s school achievement). Some features of the causal analysis are worth noting. First, we note that the variables X₁ and X7 play an important role in the system. Direct paths are connected from X₁ to all the dependent variables except X5. This indicates the direct effects of parent’s education on psychological and physical home environments, learning behaviors, and school achievement. The variable X6, children’s behaviors for school learning, proves to be a major mediating variable in the model. The figure shows that most of the independent variables exert their influence on school achievement through the intermediation of learning behaviors. Second, the economic status of home shows no direct effect on school achievement. However, it directly affects home environments, which in turn influence school achievement indirectly through the paths to self-concept and learning behaviors. Another feature in the diagram is that there are relatively large residual paths to the dependent variables, especially to psychological home environment. This means that some relevant variables were missed in the model and thus large amounts of variances of the dependent variables are explained by the variables not included in the model. Some limitations were discussed in relation to the use of path analysis method. It was also pointed that path analysis is not a method for discovering or demonstrating causals, but an analytic tool for theory testing and causal structures.