Breast cancer has the highest incidence among cancers in women, in India and worldwide. Screening and early detection play a large role in reducing mortality as breast cancer can be cured if it is detected in the early stages. Mammography is considered the gold standard in screening, but it is not useful for younger women due to low sensitivity with denser breasts and its harmful X-rays can cause an increase in the risk of cancer if used frequently. Sonomammography is typically used in correlation. Incidence rates are rising in younger women as compared to previous decades, due to changes from environmental pollutants and socioeconomic reasons. This is causing a relook at thermography for low cost and non-harmful screening. In this paper, an automated thermographic screening tool is used to classify 108 subjects from the patient database of Central Diagnostic Research Foundation, a diagnostic clinic. In addition to classification, the location of the suspected tumor is also highlighted on the thermography images. The results are promising with 100% sensitivity and 73% specificity. The algorithm used is novel, which combines features obtained from the temperature distribution of the subject, in a personalized manner, to classify as well as localize the tumor.