Biodiesel production from different feedstocks is one of the effective ways to anticipate the problems related with fuel crisis and environmental issues. In this study, the response surface methodology (RSM)-based Box-Behnken experimental design (BBD) is used to optimize the parameters of biodiesel production for the blend of Jatropha-algae oil such as molar ratio, temperature, reaction time, and catalyst concentration. A significant quadratic regression model (p < 0.0001) with R-2 of 0.9867 was achieved under the condition of molar ratio 6-12%, KOH 0-2%, reaction time 60-180 min, and temperature 35-55 degrees C. The artificial neural network (ANN) with the Levenberg-Marquardt algorithm was also trained in this study with the topology 4-10-1 with a predicted correlation coefficient of 0.9976. From the results, it is also found that the predicted values of yield are in good agreement with the results of RSM correlations.