In this study, the effect of starch concentration (5, 7.5 and 10 %) and temperature (60, 70 and 80 A degrees C) on the creep and recovery behaviour of grape molasses was investigated. Adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) models were established for the prediction of the compliance values (J(t)) based on temperature, starch concentration and time of the creep or recovery phases. The root mean square error, mean absolute error and R (2) values were used for the comparison of the models which showed that the ANFIS model performed better than the ANN model for the desired purpose. The Burger model fitted the J(t) versus time data with R (2) values ranging from 0.987 to 0.999. Response surface methodology (RSM) was performed to investigate the dependency of the creep (G (0) , G (1) , n (0) and n (1) ) and recovery (J (KV) , B, C, J (max) , J (a) and % recovery) parameters to temperature and starch concentration. As a result of this study, it was observed that deformation of the grape molasses samples increased with decrease in starch concentration and increase in temperature. The gel strength (S) values of the samples were also calculated and modelled by RSM. As increase in starch concentration caused an increase in S value, there was an inverse proportion between the temperature and S value.