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Simple Summary: TIL scoring has been recommended as a biomarker in routine clinical practice in breast cancer patients. Currently, the standard of care for early breast cancer is neoadjuvant treatment. Recent studies have demonstrated the additional predictive value of TIL scoring to the residual cancer burden after neoadjuvant treatment. Although guidelines have been published, the reliability of this biomarker in treated tumor samples has not yet been evaluated. Here, we show that there is good inter-pathologist reproducibility for TIL scoring in patients with clear residual tumor tissue. However, in patients with a (near-)complete response, there is not. This is significant because this demonstrates that it could be a reliable biomarker and help guide adjuvant treatment decisions. Neoadjuvant chemotherapy (NAC) is now the standard of care for patients with locally advanced breast cancer (BC). TIL scoring is prognostic and adds predictive value to the residual cancer burden evaluation after NAC. However, NAC induces changes in the tumor, and the reliability of TIL scoring in post-NAC samples has not yet been studied. H&E- and dual CD3/CD20 chromogenic IHC-stained tissues were scored for stromal and intra-tumoral TIL by two experienced pathologists on pre- and post-treatment BC tissues. Digital TIL scoring was performed using the HALO® image analysis software (version 2.2). In patients with residual disease, we show a good inter-pathologist correlation for stromal TIL on H&E-stained tissues (CCC value 0.73). A good correlation for scoring with both staining methods (CCC 0.81) and the digital TIL scoring (CCC 0.77) was also observed. Overall concordance for TIL scoring in patients with a complete response was however poor. This study reveals there is good reliability for TIL scoring in patients with detectable residual tumors after NAC treatment, which is comparable to the scoring of untreated breast cancer patients. Based on the good consistency observed with digital TIL scoring, the development of a validated algorithm in the future might be advantageous. [ABSTRACT FROM AUTHOR]