Bovine brucellosis is significant infectious disease caused primarily by Brucella abortus, Brucella melitensis, and Brucella suis, instigating noteworthy economic losses and public health risks owing to their zoonotic potential. Brucellosis is regarded as most prevalent zoonoses in world by different international organizations. Brucella is extremely contagious and transmitted via direct contact by Brucella carriers or via indirect contact upon animal’s consumption of contaminated excrement or forages carrying abundant bacteria, usually shed via infected animals. Brucella replication triggers invasion of inflammatory cells, vasculitis, trophoblastic necrosis, and allantochorion ulceration. Consequently, compromised fetal-maternal metabolic exchanges led to abortion. Traditional diagnostic techniques including culture, serological tests and nucleic acid amplification tests are employed for disease diagnosis. However, these methods present several drawbacks, such as high costs, labor-intensive processes, lower specificity and sensitivity, time consumption, and challenges in differentiating between past and active infections. Next-generation sequencing (NGS) is an innovative diagnostic technology that theoretically has the capacity to detect all microorganisms, including brucellosis, in samples containing DNA as their genetic material. Machine learning (ML) is a contemporary analytical platform that has the potential to improve diagnostic accuracy for brucellosis. Biosecurity measures and vaccination are essential for infection control and the protection of both animal and human health.