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The derived values of ANFIS model output are found within the range after being verified practically. Coefficient of determination and Correlation coefficient is 0.9310 and 0.9649 respectively. This model has been verified by testing and actual data set with the average percentage accuracy achieved is 95.97%. The purpose of this research is to gain the advantage of the capabilities of both Fuzzy systems, which is a rule-based approach and neural network which focus on the network training. The purpose of this study is to find the makespan estimation in advance if processing time of machines is known. On the basis of this algorithm, adaptive neuro-fuzzy inference system model is made to predict the makespan of the jobs. Assembly shop makespan is calculated by Nawaz, Enscor, and Ham (NEH) algorithm. adaptive neuro-fuzzy inference system (ANFIS) applied to the n job, m machine real flexible manufacturing system assembly shop problem with the objective of prediction of makespan. This paper considers the use of combination of neural networks and fuzzy system i.e.