Background: Muscle-invasive bladder cancer (MIBC) is universally classified as high-grade urothelial carcinoma, precluding the use of histological grading alone for prognostication. However, specific morphological features of MIBC may provide useful information to guide treatment decisions. In the last decade, there has been increasing interest in genetic profiling of MIBC. Objective: The aim of the study is to validate the use of Lund Classification in attributing phenotype to large series with extreme reliability and reproducibility compared to all histological sections in the clinical practice. Methods: We performed a molecular profiling study on a large, consecutive cohort of MIBC cases using a straightforward immunohistochemical algorithm aligned with the Lund Classification. Results: We evaluated 450 MIBC cases. In a subgroup of 103 patients, we assessed the concordance between transurethral resection of bladder tumor (TURBT) specimens and cystectomy on paired samples. Luminal tumor types showed a statistically significant association with the usual histotype, while basal and NULL types were more frequently associated with variant histotypes (p < 0.0001). A stromal lymphocytic infiltrate ≥10% was more commonly observed in basal types (p < 0.0001). Basal types also exhibited higher positive rates of human epidermal growth factor receptor-2 (HER2/neu) positivity, while luminal types were more likely to be positive for tumor suppressor protein p53. Luminal types have demonstrated longer survival compared to their basal and NULL counterparts. In the concordance analysis, tumor type assignment based on TURBT showed sensitivity, specificity, and both positive and negative predictive values of 100% for basal and NULL types. The predictive accuracy for luminal types on TURBT ranged between 89.5% and 98.2%. Conclusion: Our findings demonstrate the feasibility of applying the Lund Classification for molecular subtyping of MIBC in routine diagnostics. The consistency in tumor type assignment between TURBT and cystectomy samples further supports the clinical utility of this approach. Tumor types significantly influenced survival outcomes, underscoring its relevance in patient stratification and personalized treatment strategies.