ObjectiveThe purpose of this study is to accurately monitor temperature during microwave hyperthermia. We propose a temperature estimation model BP‐Nakagami based on neural network for Nakagami distribution.MethodsIn this work, we designed the microwave hyperthermia experiment of fresh ex vivo pork tissue and phantom, collected ultrasonic backscatter data at different temperatures, modeled these data using Nakagami distribution, and calculated Nakagami distribution parameter m. A neural network model was built to train the relationship between Nakagami distribution parameter m and temperature, and a BP‐Nakagami temperature model with good fitting was obtained. The temperature model is used to draw the two‐dimensional temperature distribution map of biological tissues in microwave hyperthermia. Finally, the temperature estimated by the model is compared with the temperature measured by thermocouples.ResultsThe error between the temperature estimated by the temperature model and the temperature measured by the thermocouple is within 1°C in the range of 25°C–50°C for ex vivo pork tissue, and the error between the temperature estimated by the temperature model and the temperature measured by the thermocouple is within 0.5°C in the range of 25°C–50°C for phantom.ConclusionsThe results show that the temperature estimation model proposed by us is an effective model for monitoring the internal temperature change of biological tissues.