The invention discloses a continuous casting breakout prediction method based on a neural network, which comprises the following steps that: step 1: the temperature data of a thermocouple on a continuous casting site is collected on line and saved; step 2: the temperature data is pre-processed; step 3: the temperature data which is collected from any one thermocouple and is pre-processed is input a single-couple time sequence network breakout prediction model, the output value of the single-couple time sequence network breakout prediction model is compared with the maximum determination threshold, and if the output value of the model is more than the maximum determination threshold, the breakout is predicted; and the method is characterized in that genetic algorithm is used for initializing the connection weights and thresholds of the single-couple time sequence network breakout prediction model. The method can improve the identification effect and the prediction precision of a continuous casting bonding breakout process so as to greatly reduce the false prediction rate and missing prediction rate.