Mastitis, infection and inflammation of the mammary gland, is the most costly disease in the dairy industry, impacting producer finances, dairy cattle well-being, and general public perception with regards to antibiotic resistance and milk and meat residues. Historically, mastitis has been monitored on a total milk somatic cell count (SCC) basis and treated once it reaches the clinical stage (i.e. garget in milk, hot swollen quarter, or sick animal). As mastitis is quite deleterious and the number one reason for antibiotic usage on dairies, improvements must be made regarding identification and treatment of this disease. Alternative monitoring systems exist that use milk differential cell counts (DCC), which recognize types and proportions of white blood cells, to identify infections during the subclinical phase of disease; however, these technologies have not reached the stage of validation required for integration into farm mastitis management programs. Improved development of these techniques to promptly identify subclinical mastitis will allow producers to treat cows earlier and more effectively, improve animal welfare, reduce milk production losses, and decrease antibiotic usage. Pilot work with an acoustic focusing flow cytometer offers an opportunity for rapid and mass handling of milk samples for DCC determination. Coupled with the help of Mastatix technology (Mastatix of New York, LLC) to determine if cows have subclinical mastitis using milk DCC, we propose to develop this technology to provide a superior alternative for mastitis detection for the dairy industry, helping to reduce the impact of clinical mastitis in the areas of economics, welfare, and antibiotic usage.