Objective The aim of this study was to determine the role of 18F-FDG PET/CT in predicting pathological response among patients diagnosed with local or locally advanced breast cancer and receiving neoadjuvant chemotherapy (NAC). Methods Basal SUVmax value were analyzed in 212 patients and 142 of these patients had posttreatment SUVmax value. Overall pathological complete response (pCRC) was defined as no evidence of residual invasive cancer in breast (pCRB) and axilla (pCRA). Basal SUVmax value of the breast (SUVmaxBI) and axilla (SUVmaxAI) and change in SUVmax of the breast (ΔSUVmaxB) and axilla (ΔSUVmaxA) were measured. The optimal cutoff value of SUVmax and ΔSUVmax were determined by receiver operating characteristic curve analysis. Results The number of patients with pCRB was 85 (40.1%), pCRA was 76 (42.5%) and pCRC was 70 (33%). In the artificial neural network-based analysis the ΔSUVmaxB (100%) was the most important variable for predicting pCRB. ΔSUVmaxA (100%) was the most important variable in estimation of pCRA. When pCRC was evaluated, the highest relation was found with ΔSUVmaxB. When the ΔSUVmaxB cutoff value for pCRB and pCRC accepted as ≤−87.9%, its sensitivity was 82.3 and 82.4%, and specificity was 72.5% and 65.9%, respectively (P < 0.001 and P < 0.001, respectively). When the ΔSUVmaxA cutoff value for pCRA and pCRC accepted as ≤−86.6%, its sensitivity was 94.3% and 97.6%, and specificity was 31.3% and 28.2%, respectively (P = 0.017 and P = 0.024, respectively). Conclusion Albeit varies according to the molecular subtypes of the breast cancer during NAC, ΔSUVmax value seems to be the most strong factor associated with pCR.