Background: The COVID-19 pandemic in India has become the biggest public health challenge. If we go by the number of confirmed cases and casualties, the situation seems to be a matter of grave concern. The lock-down measures and social-distancing practices have played an important role in impeding the spread of COVID-19. However, accurate forecasting is required to prepare the healthcare-system for future plan-of-action. Objectives: The present study aims to predict the trends in the outbreak of COVID-19 in India, by forecasting on the basis of publicly-available data. Methods: The data has been obtained from https://www. covid19india.org, https://www.worldometers.info/coronavirus and ICMR reported publiclyavailable information on COVID-19. The number of confirmed cases are growing exponentially as per the real-time-data. For forecasting the trends in terms of confirmed, active, recovered, and death cases by using the autoregressive-integrated-moving-averages (ARIMA) model. Results: Findings reveal the estimated value of the point-forecast for total confirmed, active, recovered, and death cases. Estimates indicate that the total confirmed cases were increasing at the rate of 3.48%, active cases at 2.92%, recovered cases at 4.09% and death cases at the rate of 3.51% daily across the country. It was also observed that the death rate was lower for the states and union territories with a higher detection rate. Conclusion: Substantial public health interventions were implemented immediately by the Government of India to control the spread of COVID-19. Due to the shortage of healthcare resources in the country, early detection is imperative along with accurate forecasting. It will help in reducing the associated cost of acute care for the majority of infected cases and unnecessary burden on the healthcare system.