Microwave (MW) sludge pretreatment enhances anaerobic digestion in terms of organics solubilization, sludge de-waterability and biogas production. The aim here is to optimize different biogas models under MW pretreatment conditions. Biogas generated from MW pretreatment of waste activated sludge under seven different MW intensities and temperatures is measured. Four biogas mathematical models, namely Modified-Gompertz (MG), Logistic-function, Reaction-Curve (RC) and exponential-rise (ER) are optimized under the seven different cases. The tunable model parameters are estimated using the gradient-based optimization technique. The performance measure of each model for the multiple experimental cases is consistent. Results reveal that the LF and MG are better fitted with experimental data than the RC and ER models. MG proves to be the best among the tested models based on percentage error (4.5%) while the RC results in the highest errors of 16.77%. However, the MG requires high computational efforts due to number of parameters. The ER, being simple and requires less computational time and at reasonable relatively errors of 10.5% is considered the best. These findings of optimal fitted model, model parameters, and its kinetics can set the stage for large scale predictive model development for biogas generation similar to those utilized for LandGEM-USEPA. (C) 2020 Published by Elsevier Ltd.