The integration of computational technologies into veterinary medicine is driving significant advancements in diagnostics, particularly in microscopy-based pathology. This chapter introduces the transformative role of computational analysis in veterinary medicine, emphasizing its ability to enhance the accuracy and efficiency of diagnostic processes. Microscopy, a fundamental tool in the diagnosis of animal diseases, traditionally relies on manual interpretation of complex tissue and cellular images. However, computational methods, such as machine learning and artificial intelligence, offer automated, precise image analysis that reduces human error and uncovers patterns not easily detected by the human eye. This evolution facilitates the detection of subtle pathological changes, improves reproducibility across laboratories, and accelerates diagnostic timelines. The chapter highlights the importance of computational analysis in revolutionizing veterinary diagnostics by providing a data-driven complement to clinical expertise. Additionally, it outlines the objectives and scope of the book, which explores advanced computational techniques and their applications in veterinary microscopy. This includes foundational knowledge of microscopy, digital imaging, and the application of machine learning, providing a comprehensive guide for veterinary professionals aiming to improve diagnostic precision and outcomes in their practice.