Metabolic disorders of dairy cows, primarily ketosis and acidosis, are one of the most significant problems in dairy herd management. Numerous studies have shown that metabolic disorders induce economic losses for milk producers due to treatment costs, reduced milk production, impaired reproduction, and ultimately increased animal excretion rates. Given the above, and for the purpose of sustainable management of the dairy herd, it is extremely important to detect as early as possible the cows that are at risk of subclinical metabolic disorders and to prevent the development of the clinical form in time. On dairy farms, milk recording is performed every month, which includes the collection of data on the productivity of dairy cattle that are in the system of breeding and selection work. The results of milk recording together with the pedigree data, the basis for calculating the breeding value of cattle and for the implementation of selection in accordance with the breeding program of each breed, also allow the breeder to improve dairy herd management and timely detection of metabolic disorders in the subclinical phase using precision dairy farming technologies. The daily content of milk fat and protein represents the basis for estimating the prevalence, with the optimal values of the ratio of milk fat and protein being 1.1 - 1.5, while the deviation from the same indicates the prevalence of acidosis or ketosis. The aim of this study was to determine the prevalence of subclinical disorders of Simmental and Holstein cows depending on the season by applying precision dairy farming technologies- that is, the results of milk recording. Our logical control dataset consisted of over 1.6 million of test day records (Holstein cows: 805,247 records/ 69,368 animals/ 4,998 farms; and Simmental cows: 845,514 records/ 78,540 animals/ 7,242 farms). Conducted analysis indicated that daily milk production, stage of lactation, parity, age at first calving, milk recording, and cattle breed significantly affected daily fat and protein content as well as F/P ratio. Also, determined higher values of F/P ratio in winter period indicates higher ketosis prevalence risk, while lower values of F/P ratio in summer period indicates higher acidosis prevalence risk. Finally, in order to more precisely predict the ketosis / acidosis prevalence in dairy cows based on milk recording data, factor that significantly affects the variability of daily fat and protein content, and consequently the fat to protein ratio as well as the prevalence risk of metabolic disorders should be taken into account.