Microwave-assisted biodiesel production from palm oil is becoming more and more important because of the greatly shortened reaction time and high energy-efficiency.In this novel research, an exptl. study was conducted to optimize the exptl. conditions of microwave-assisted biodiesel productionResponse surface methodol. (RSM), back propagation artificial neural network (BP-ANN) and Genetic algorithm improved BP-ANN (BPANN-GA) and were established and compared to optimize four operating parameters, including methanol/oil molar ratio (5:1-15:1), catalyst amount (0.75 -1.25 weight%), temperature (60-70°C) and microwave time (20 -50 min).RSM, BP-ANN and BPANN-GA models were considered to be reliable in predicting biodiesel yield, BPANN-GA model (R2 = 0.9957) showed better accuracy than the RSM model (R2 = 0.9823) and BP-ANN model (R2 = 0.9867).The optimized process parameters were 14.9 methanol/oil molar ratio, 0.84 weight% catalyst amount, 69°C temperature and microwave time of 49.3 min, the corresponding yield was 98.15%.The produced biodiesel properties were compared with ASTM D6571 standardsThe results of the research are constructive for the optimization of microwave-assisted biodiesel exptl. conditions when processing a small sample database.