Carbon fiber reinforced polymer is widely used in high-tech fields such as aerospace, fatigue damage will occur during service, it will bury potential safety hazards. Therefore, its health needs to be monitored, and damage probability imaging algorithms can be used to intuitively reflect structural health. However, the traditional damage probability imaging algorithms have a high damage probability in the non-damaged area and it is difficult to accurately locate the damage. In view of the above problems, a damage probability imaging algorithm based on Lamb wave energy and time of flight is proposed. The area measured is evenly divided into N pixels, calculate the Lamb wave energy and time of flight damage factor of each channel, determine and superimpose the probability value in the affected area of each channel damage factor, and obtain the damage probability of each pixel and image it. The experimental results show that compared with the frequently-used damage probability imaging algorithms based on energy damage factor and cross-correlation damage factor, the proposed method can intuitively reflect the defects of carbon fiber reinforced polymer, and the recognition effect is better, the imaging error is significantly reduced, the error is reduced by 4. 420, 2. 117, 2. 055 and 4. 732, 2. 380, 2. 647 respectively, which can identify defects more accurately and guarantee the safe application of carbon fiber reinforced polymer structure effectively.