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This paper presents the hybridized fuzzy-neural predictive intelligent (HFNPI) based approach for predicting FinFET model. The proposed model is an improved approach over artificial neural network (ANN) model and adaptive neuro fuzzy inference system (ANFIS) model that provides optimum model parameters. In this paper, the challenge of optimization of large number of parameters is reduced. It assesses the performance of resultant structure on the basis of selected RF figure-of-merit. Based on the application requirements, RF figure-of-merit such as fT and fmax are used as appropriate performance parameters to analyse the device performance. The framework for the HFNPI model is underlapped FinFET structural/process parameters. The mean prediction error was found 2.8 × 10−4 GHz. The comparative analysis of HFNPI with ANN and ANFIS model is done. It is found that combination of fuzzy and neural logic shows better result rather than individual ANFIS and ANN model to redevelop the model and increase the number of inputs. [ABSTRACT FROM AUTHOR]