In order to increase the accuracy of the Classification And Regression Tree (CART) regression algorithm, we propose an improved CART regression algorithm based on Extreme Learning Machine (ELM-CART for short). The proposed algorithm mainly applies the ELM for modeling at each leaf node in the process of creating a CART, which can get the true regression prediction value, improve the generalization ability, and compensate for such disadvantages of the CART regression algorithm as easy overfitting and constant predictive output. The experimental results show that the proposed algorithm can effectively improve the prediction accuracy of target data in regression analysis, and its accuracy is higher than that of the counterparts.