This study employs the CARR (Conditional Auto Regressive Range) and GARCH models to predict the volatility of the EU Carbon Credit price and compares the prediction power of the two models. Based on various volatility estimation methods, this work examines the impact of natural gas price, Brent crude oil price and coal price on the volatility of EU Carbon Credit price. This investigation also attempts to obtain the assessing standard of optimal parameter estimation value by testing CARR and GARCH models using weekly range and weekly return. Additionally, this study compares the forecasting ability of CARR model with that of GARCH model on out-of-sample data by EU Carbon Credit price. The empirical results show that the estimated parameters obtained from CARRX(1,1) and GARCH(1,1) are the most concise ones, which confirms with the finding of Chou (2005). Furthermore, both the CARR model and GARCH model prove that Energy price has a significant impact on EU Carbon Credit price, and there is a leverage effect of energy price on EU carbon credit price. This study also finds that when negative energy news and other events occurred, the energy price influences the EU Carbon Credit price immediately, and the effect will lasts for one week. Moreover, the volatility of EU Carbon Credit price also increases indirectly. Regarding the forecasting ability on EU carbon credit price, this investigation finds that the accuracy and conciseness of the forecasting volatility implemented by CARR model outperforms that employed by GARCH model.