Background and Objective: The COVID-19 pandemic caused approximately 11,421,822 laboratory confirmed cases globally with 196,750 confirmed cases in South Africa by the 6th of July 2020. Coronavirus is transmitted from one person to another even before any symptoms appear, thus posing a severe threat to the society as a whole. This study is aimed at coming up with an ARIMA model to predict daily COVID-19 disease cases in South Africa using data from online sources. Materials and Methods: The

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... y used online data on daily COVID-19 reported cases in South Africa (SA) recorded from 6 March 2020 to the 6th of July 2020. Time series analysis is used to investigate the trend in the daily COVID-19 disease cases leading to the Auto-Regressive Integrated Moving Average (ARIMA) model. Results: The time plot of the series suggests the need for differencing of the data up to the second-order to achieve a stationary time series. The best candidate model was an ARIMA(7,2,0). Residuals for the selected model are non-correlated and normally distributed with mean zero with a constant variance as expected in a good model. The fitted model predicted a continuous increase in the daily COVID-19 disease cases for the next 20 days ahead to day 143 with slight falls at a few time points.Conclusion: The results showed that ARIMA models can be applied to COVID-19 patterns in South Afriva. The model forecasted a continuous increase in the daily COVID-19 cases in South Africa. These results are important for public health planning in order combat the pandemic.