This study presents a hybrid approach, which provides a multi-criterial vertical handover decision support using a genetic neuro-fuzzy controller. A methodology for developing the genetic neuro-fuzzy controller was considered. The architecture of the controller was elaborated. Linguistic variables, terms and membership functions for input and output values were defined. A rule base and mathematical models of the controller were considered. An Adaptive Neuro-fuzzy Inference System (ANFIS) on the base of the fuzzy-controller was developed. A genetic algorithm to improve the rule base was suggested. The efficiency of the proposed handover neuro-fuzzy controller was checked by performing the computer simulation in Matlab program. The genetic neuro-fuzzy controller can be utilized in 5G networks of the Internet of Things in order to improve the process of vertical handover, while merging these three techniques of fuzzy systems, neural networks and genetic algorithms can outcome in a much more efficient method.