Breast cancer identification based on imaging system is developed until now. One of the modalities to identifying breast cancer using thermal imaging through energy heat intensity that emitted by cancer nodule. The difference of heat temperature on cancer nodule compare with other area shows that there is an abnormality in it. Thermal imaging is a heat image which is has no clear edge (multiresolusi). In this research, we using ANN ( Algorithm Aritificial Network ) to analyse thermal imaging on breast cancer where ANN input structure optimized by implementing wavelet and statistic method. The purpose is to generate information that inform about breast abnormal and size of cancer nodule. This research was done using 12 rats as a model and divided by 2 groups. 5 rats have no treatment, while the rest inducted with 10 times of 20 mg/BB of DMBA ( 7.12 dimenthyl benz (?) anthracene ). Treatment is carried out for 2 month and checked for the cancer nodule every week. Testing as a gold standard is done by palpamasi and Patologis Anatomi (PA). The result shows 87.5% sensitivity with 57% specivity. In group 2 shows that all subjects 100% infected by cancer with 70% cancer potential and 30% has a high temperature ( neoplasma ). The smallest size of cancer nodules that can be detected is 1.5 mm x 5.85 mm.