For specific applications of infrared thermography (IRT) in the field of human medicine diagnosis, well defined standard operating procedures are used (e.g. controlled ambient conditions). In contrast, when IRT is used in the veterinary and animal science field, examinations are not always performed under controlled ambient conditions. This leads to unavoidable influences to the surface temperatures measured with IRT. This paper quantifies this effect and proposes a novel modelling and correction approach. This approach results in a significant increase in the quality of the data and provides a more accurate measurement of IRT for assessing animal health and welfare.