Optimal performance of robot manipulators can be achieved only by utilizing advanced control algorithms. However, precise control of robot motion requires the use of accurate dynamic models, which are very complicated due to varying arm geometric configuration, uncertain effects of load handling on the dynamic stability of the arm, and the high degree of nonlinearty and coupling exhibited between different links. Therefore, an efficient and fast method for on-line tuning of robot dynamic parameters must be devised. In this work a simplified model based on Lagrange-Euler dynamics is developed. The proposed method is simple and systematic for the extraction and identification of robot dynamic parameters. The dynamic parameters are then formulated as a regression model. This model is used to generate the closed-form solution of the dynamics. The analysis in this work is based on a set of compiled data for the Stanford arm to facilitate the study of the dynamic performance and closed-loop solutions of robot manipulators. For the derivation of the dynamics MAPLE (symbolic computer algebra language) is used.