Aim: To forecast the monthly percentage of Holstein cows and heifers at a high-input dairy farm experiencing retained placenta (RP), puerperal metritis (PM), and clinical ketosis (CK). Methods: An autoregressive integrated moving average (ARIMA) model was employed to predict future monthly cases of these diseases using time series data. These puerperal diseases were observed on a single dairy farm with 2560 to 3300 milking cows over seven years, from 2014 to 2020. Results: The highest predicted RP incidence in cows was in May (11.3%; 95% CI = 6.3-16.4), while the lowest was in November (5.4%; 95% CI = 0.5-10.4). For heifers, the peak predicted RP occurrence was in August (20.6%; 95% CI= 11.0-23.1), and the lowest was in December (10.5%; 95% CI= 7.9-13.0). The highest projected CK occurrence in cows was in June (3.0%; 95% CI = 1.8-4.3), and the lowest was in November (1.1%; 95% CI = -0.1-2.4). For heifers, CK was most likely in May (2.7%; 95% CI= 0.9-4.5) and least in December (0.7%; 95% CI=-1.1-2.5). Conclusions: Both cows and heifers showed an increasing trend in RP, PM, and CK during summer months; ARIMA models effectively tracked disease trends throughout the year and can aid in health management decisions for dairy cows.