Urinary bladder cancer, the tenth most common cancer globally, exhibits significant variability in the reported expression of estrogen receptor alpha (ERα), a key prognostic marker. Accurate and reproducible assessment of ERα is critical for elucidating its role in bladder cancer biology and identifying therapeutic targets. Aim: This study compared manual scoring with automated analysis using ImmunoRatio software for quantifying ERα expression in a chemically induced bladder cancer model in rats, using N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN). Methods: Twenty male Wistar rats were randomly assigned to two groups: a control group (n=8) and a group treated with BBN (BBN; n=12), administered in drinking water at 0.05% for 20 weeks. Animals were sacrificed and urinary bladders were collected for macroscopic and microscopic evaluation. Samples underwent standard histological processing and immunohistochemical analysis to assess ERα expression, quantified both manually and automatically. Results: The immunoexpression of ERα, detected by ImmunoRatio was found to be significantly higher than that obtained through manual counting in both groups (p < 0.0001). ImmunoRatio analysis indicated a higher ERα expression in the control group than in the BBN group (p < 0.001), whereas manual counting showed the opposite tendency, without statistical significance (p > 0.05). Conclusion: Our findings demonstrated that ImmunoRatio resulted in significantly higher ERα immunoexpression values than manual counting in both control and BBN-treated groups, with inconsistent group-wise trends between methods. These findings suggest that, although digital pathology tools offer advantages in standardization and reproducibility, their application requires tissue-specific calibration and validation to ensure accurate and reliable biomarker quantification.