Active thermography is an efficient tool for defect detection and characterization as it does not change the properties of tested materials. The detection and characterization process involves heating a sample and then analysing the thermal response. In this paper, a long heating pulse was used on samples with a low thermal diffusivity and artificially created holes of various depths. As a result of the experiments, heating and cooling curves were obtained. These curves, which describe local characteristics of the material, are recognized using a classification tree and divided into categories depending on the material thickness (hole depths). Two advantages of the proposed use of classification trees are: an in-built mechanism for feature selection and a strong reduction in the dimensions of the pattern. Based on the experimental study, it can be concluded that classification trees are a useful tool for the thinning detection of homogeneous material.