Conventional bacteriological methods to establish bacterial burden and distribution in infected tissues in vivo animal models typically require extensive bacteriological procedures and therefore are time consuming. An alternative approach has been suggested to use optical markers, such as luciferases, to labeled pathogens and monitor their progress and distribution in real time. The objective of the work presented in this document was to validate the use of Biophotonic Imaging (BI) through in vitro studies as a first step toward the development of in vivo models to study infectious disease in the bovine. For example, the feasibility of detecting bioluminescent Escherichia coli (E. coli-lux) from within the different bovine reproductive tract segments was studied. Up to 17 % transference of photonic emissions (PE) was detected through the reproductive tract, suggesting that in vivo or in situ models may provide a novel approach for in real time screening of uterine infections in large farm animal models. Further in vitro research conducted toward the development of approaches for non invasive detection of lux-bacteria in bovine mastitis models demonstrated that detection through the bovine mammary gland might be limited due to tissue thickness and density. However, imaging of Staphylococcus aureus (S. aureus)-lux presence in teat-end skin wound in vitro models demonstrated promising results. Furthermore, trials demonstrated that imaging of lux-bacteria in milk samples, as means to estimate bacterial cell numbers (CFU), represent an efficient model to monitor bacterial progression in vivo mastitis models. According to these findings, the efficacy of an intramammary antimicrobial agent was evaluated in real time using S. aureus-lux in vivo mastitis models conducted in lactating dairy cows. Photonic emissions from milk samples collected from challenged quarters with S. aureus-lux resulted to be an excellent predictor of CFU, as demonstrated by the high and positive correlation (0.99; P < 0.0001) between CFU and PE. In addition, BI provided in real time information regarding spatial distribution of S. aureus-lux in infected mammary gland quarters ex vivo. Collectively, this date positions BI as novel and promising tool to improve current bacteriological methods to better understand pathogenesis of bovine mastitis infections.