Background: We aimed to create a model of radiological and pathological criteria able to predict the upgrade rate of low-grade ductal carcinoma in situ (DCIS) to invasive carcinoma, in patients undergoing vacuum-assisted breast biopsy (VABB) and subsequent surgical excision. Methods: 3100 VABBs were retrospectively reviewed among which we reported 295 low-grade DCIS who subsequently underwent surgery. The association between patients’ features and the upgrade rate to invasive breast cancer (IBC) was evaluated by univariate analysis. Finally, we developed a predictive multivariable model based on the features which were significantly associated with the univariate analysis outcome. Results: the upgrade rate to invasive carcinoma was 10.8 %. At univariate analysis, the risk of upgrade was significantly lower in the absence of post- biopsy residual lesion (p<0.001), age > 50 (p=0.029), and in presence of low-grade DCIS only in specimens with microcalcifications (p=0.002). According to the final multivariable model, the predicted probability of diagnostic underestimation for a patient with all the three favourable features selected at univariate analysis was 1% (95% CI: 0.3%-4%). Conclusions: An easy to use predictive model of radiological and pathological criteria is able to identify patients with low-grade carcinoma in situ with low risk of upstaging to infiltrating carcinomas.