In this study, neuro-fuzzy control of a thermoelectric head cooler system (thermoelectric helmet) is developed for brain hypothermia applications. Hypothermia is a medical treatment method of protecting the brain, in which the temperature of the brain drops below the critical level for reducing oxygen consumption of tissues. The brain should be kept at a certain temperature by a suitable control for hypothermia applications. The temperature of the thermoelectric head cooler system changes according to the current intensity supplied. The control of the thermoelectric head cooler system was performed according to the initial membership functions, which was determined by an expert using fuzzy logic control. The system was modeled by an adaptive neuro-fuzzy inference system (ANFIS). The data were then entered into the system and new membership functions were determined. By this way, learning ability of the artificial neural network and the abilities of fuzzy logic, such as decision making, were combined and a more effective solution was developed. The system software can be reprogrammed with the new membership functions.