In the present paper, applicability and capability of A.I techniques for effort estimation prediction has been investigated. It is seen that neuro fuzzy models are very robust, characterized by fast computation, capable of handling the distorted data. Due to the presence of data non linearity, it is an efficient quantitative tool to predict effort estimation. The one hidden layer network has been developed named as OHLANFIS using MATLAB simulation environment. Here the initial parameters of the OHLANFIS are identified using the subtractive clustering method. Parameters of the Gaussian membership function are optimally determined using the hybrid learning algorithm. From the analysis it is seen that the Effort Estimation prediction model developed using OHLANFIS technique has been able to perform well over normal ANFIS Model.