The aim of the current work is to predict fatigue crack growth life of 8090 T651 Al-alloy under the influence of load ratio by applying adaptive neuro-fuzzy inference system (ANFIS) technique. The model has been trained by minimization of root mean square error (RMSE) principle. It has been observed that the proposed model predicts well the fatigue crack growth life of the alloy with 0.801% deviation in comparison to experimental results.