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In the modeling approach of Jupiter’s radiation belt, the accurate calculation of magnetic coordinates from geographic coordinates is the basis. In the previous studies, the L-shell parameters are always calculated based on the assumption of a dipole field though the accuracy of this method is low. We present a new L-shell calculation method based on the magnetic field lines tracing method and ANN (Artificial Neural Network). In this method, a compromise between calculation accuracy and speed is achieved. This method consists of a classifier and a predictor. The Classifier is a BP (Back Propagation) ANN based on AdaBoost algorithm and the Predictor is a BP ANN optimized by GA (Genetic Algorithm). The Classifier is used to identify whether the coordinates are within Jupiter’s inner magnetosphere. If so, the Predictor is used to calculate the L-shell parameters. The error rates of the Classifier and the Predictor are 3 and 7%, relatively. In an example of the Juno’s orbit, the calculation speed of this ANN-based method is about 3 orders higher than that based on the magnetic field lines tracing method.