The battery remaining discharge energy has a significant influence on the remaining driving range of pure electric vehicles; therefore, it requires precise estimation. This paper introduces a novel approach for battery remaining discharge energy estimation based on the accurate prediction of future operating conditions. In the proposed battery remaining discharge energy estimation algorithm, the battery future power output and temperature change rate are firstly predicted according to the historical data. An equivalent circuit model, with the parameters identified using the recursive least-squares algorithm, is applied to simulate the battery voltage response. Battery remaining discharge energy is then estimated based on the iterative prediction of battery states (including the state of charge, temperature, battery model parameter variations and voltage response) in the future discharge process. The performance of the prediction-based remaining discharge energy estimation approach is validated under dynamic current and temperature conditions. The results demonstrate that the proposed method can guarantee desirable accuracy and robustness in battery remaining discharge energy estimation under dynamic operating conditions, exhibiting its potential for practical applications.