In this paper a novel neural fuzzy inference network (NFIN) it is proposed. The NFIN represent a modified Takagi-Sugeno-Kang (TSK) type fuzzy rule based model with neural network learning ability. The rules in the NFIN are created and adapted in an on-line learning algorithm. The structure learning together with the parameter learning forms the learning algorithms for the neural fuzzy network. It is proved that NFIN can greatly reduce the training time, avoid the overtuned phenomenon and has perfect regulation ability.