This paper describes a practical system to classify material temperature responses by composition of curve fitting and neuro-fuzzy inference. There are problems with a classification system which utilizes temperature responses. It requires too much time to approach the steady state of temperature response and it has to be filtered to remove the noise which occurs in experiments. Thus, this paper proposes a practical method using curve fitting only for transient state to remove the above problems of time and noise. Using the neuro-fuzzy system, the thermal conductivity of the material can be inferred on various ambient temperatures. So the material can be classified via its inferred thermal conductivity. To realize the system, we designed a contact sensor which has a similar structure with human finger, implemented a hardware system, and developed a classification software of curve fitting and neuro-fuzzy algorithm.