Abstract: Based on the experiment data from biodiesel production in laboratory, an artificial neural network (ANN) model was developed for predicting the biodiesel conversion by using BP (Back-Propagation) algorithm. The appropriate topology of ANN was obtained. The learning rate, the momentum factor and overfitting phenomena in BP network were discussed. It was shown that the ANN model can correlate and predict the biodiesel conversion accurately after comparing the prediction results with the experiment data. The average prediction error of the biodiesel conversion was 1.917%，and the correlation coefficient R was equal to 0.9996. The ANN model was optimized by incorporating genetic algorithm. Optimal operation conditions of the biodiesel production were obtained by using the ANN model developed.