Abstract: A three-layer feed forward neural network was used to predict the rate of adsorption of textile dye direct blue 86 using microwave assisted activated carbon. In the present study, the Levenberg-Marquardt back-propagation algorithm was used to train the neural network at various experimental conditions. The pH, contact time, initial dye concentration, adsorbent dose and temperature were chosen as the input variables whereas, the dye uptake capacity was considered as the output variable. The tan sigmoid and linear transfer functions had been selected to train the hidden and output layer of the network, respectively. According to Levenberg-Marquardt back-propagation algorithm the optimum number of neurons was found to be eight. The predicted and experimental values of the desired output variables were in good agreement with each other with a correlation coefficient value of 0.982.