The transcriptome has considerable potential for improving biopsy diagnoses. However, to realize this potential the relationship between the molecular phenotype of disease and histopathology must be established. We assessed 186 consecutive clinically indicated kidney transplant biopsies using microarrays, and built a classifier to distinguish rejection from nonrejection using predictive analysis of microarrays (PAM). Most genes selected by PAM were interferon-γ—inducible or cytotoxic T-cell associated, for example, CXCL9, CXCL11, GBP1 and INDO. We then compared the PAM diagnoses to those from histopathology, which are based on the Banff diagnostic criteria. Disagreement occurred in approximately 20% of diagnoses, principally because of idiosyncratic limitations in the histopathology scoring system. The problematic diagnosis of ‘borderline rejection’ was resolved by PAM into two distinct classes, rejection and nonrejection. The diagnostic discrepancies between Banff and PAM in these cases were largely due to the Banff system's requirement for a tubulitis threshold in defining rejection. By examining the discrepancies between gene expression and histopathology, we provide external validation of the main features of the histopathology diagnostic criteria (the Banff consensus system), recommend improvements and outline a pathway for introducing molecular measurements.