Aiming at the shortcomings of the current widely used contact and noncontact tube metal temperature measurement technology and the method of diagnosing the degree of coking of the furnace tube, a new tube metal temperature (TMT) measurement method and a method of diagnosing the coking degree of the furnace tube and predicting the coking trend were introduced in this study. Also, referring to the new generation of intelligent temperature-measuring devices developed for measuring TMT, an intelligent temperature-processing algorithm based on machine learning and neural network was proposed. This method not only improved the accuracy of measuring TMT and the accuracy of tube identification but also reduced the technical cost of TMT measurement to some extent.