Background/Objectives: Diffuse large B-cell lymphoma (DLBCL) is an aggressive lymphoma and one of the most common hematological neoplasia. Entropy is a statistical measure of randomness that can be used to characterize the texture of an input image and measure tissue complexity. Methods: Image processing and computer vision analysis were performed on a series of 114 diagnostic DLBCL cases and 44 reactive lymphoid tissues stained with hematoxylin & eosin (H&E). Histological entropy was measured to differentiate between reactive lymphoid tissue and DLBCL and predict clinical evolution. Gene expression analysis using the NanoString nCounter PanCancer Immune Profiling Panel was performed in 29 cases. Results: Comparison with reactive lymphoid tissue, DLBCL was characterized by lower entropy (7.3 ± 0.2 vs. 6.8 ± 0.6; P < 0.001, respectively). Within the DLBCL diagnostic category and at patient-level analysis, higher entropy was associated with poor overall survival and death events within the first 2 years (hazard-risk = 2.4, P = 0.004) and lower entropy with a moderate and more favorable outcome (hazard-risk = 0.4, P = 0.004). High entropy was also correlated with ECOG performance status ≥ 2, lower protein expression of apoptosis markers of cPARP and cCASP3, and upregulation and downregulation of specific immuno-oncology genes. Conclusion: The histological evaluation of entropy is useful for both the differential diagnosis of reactive lymphoid tissue and DLBCL and can be used as a predictor factor of DLBCL prognosis.