The air flow laser fusion technique has the characteristics of noncontact and nondestructive. A controlled air flow laser detection (CAFLD) method was proposed, which was based on the highprecision detection of micro deformation by laser, flexible onoff control and noncontact of the air flow. Five components were included in the air flow laser detection platform: laser ranging system, air force generation system, lifting testing bed system, force sensing system, and control and information processing system. The feasibility of chicken breast tenderness detection by using the CAFLD technique was explored. Three modes: transient (dynamic), creeprecovery (static) and stress relaxation (static) were adopted. The support vector machine and global variable partial least square algorithm were used to qualitatively identify and quantitatively predict the tenderness of chicken breast. The results demonstrated that the three modes combined with different preprocessing algorithms could carry out the qualitative discrimination of chicken tenderness, in which the transient mode had the best classification effect compared with the static modes. S-G convolution smoothing algorithm showed the best preprocessing performance. The classification accuracy (tender or hard) of the calibration set was 1 and 0.98, respectively, the Matthews correlation coefficient was 0.97; the classification accuracy (tender or hard) of the verification set was up to 0.95 and 0.84. For quantitative prediction of chicken tenderness, the S-G convolution smoothing algorithm was the optimum on improvement of the signaltonoise ratio. The transient had the best prediction effect, the correlation coefficients of calibration set and validation set were 0.948 and 0.913, respectively, the root mean square error was 0.736N and 1.013N, respectively. Because tenderness was the quality of meat which was shown by the difference muscle fiber structure. it can be inferred that the dynamic mode was more suitable than the static mode in predicting the quality caused by tissue structure. The application of CAFLD technique in meat quality multimodal evaluation was researched. It would provide a new solution method in meat detection field, and also had important reference significance for broadening the application field of the CAFLD technique.