Infrared thermal imaging is a non-destructive, non-invasive technique that has shown to be effective in the detection and pre-clinical diagnosis of a variety of disorders. Nowadays, some medical applications have already been successfully implemented in pre-clinic diagnostics using thermography based on AI algorithms to support decision-based medical tasks. Though, the massive amount of image types, disease variety, and numerous individual anatomical features of the human body continue to give researchers more challenging jobs that still need to be solved. This paper proposes a novel methodology using a convolutional neural network (CNN) for analyzing with high accuracy infrared thermal images from the spine region for quick screening and disease classification of patients.