Foodborne diseases caused by undercooked poultry products are noteworthy problems that have motivated research into the assessment of the endpoint temperature in meat. In this research, a novel infrared and laser range imaging system was proposed to estimate the internal cooking temperature of chicken breasts. It consisted of three subsystems: an IR imaging system, a laser range system, and an artificial neural network modeling system. Our experiments showed that geometric variables played an important role in the endpoint temperature estimation. The accuracy achieved by our system was 1.54° C for mean absolute error, 2% for mean absolute percent error, and 3.08(° C)2 for mean square error. The combined IR and laser range imaging system showed the potential for real-time, non-contact and non-invasive estimation of the internal cooking temperature in meat for enhanced food quality and safety.