Time series analysis is a process which deals with data to identify trends and forecast future happening. The data used in this analysis is known time series data which is in a time interval format. The data was used is based on the data which is taken in a different interval of time, known as time-series data. Balancing of demand and supply is based on the accurate prediction of sales in future, if there is a lack of efficient forecasting than it can a challenge to run the business and make a good profit. Time-series forecasting is one of the most commonly used approaches in day-to-day in many organizations. Marketing research also uses time-series data to find their future predictions. Its main strength is to study the change of various event in time so that it can be a strong tool for marketers. Approaches of time series analysis are autoregressive integrated moving average(ARIMA), seasonal autoregressive integrated moving average(SARIMA), autoregressive moving average(ARMA), moving average(MA) and autoregression(AR). This paper consists of predicting the monthly sales of champagne by using time series and will also predict the future monthly sales of champagne. ARIMA and SARIMAX model was used for forecasting and predicted the sales of champagne for 10 years. Champagne dataset was used in this research and using time series, predicting model was prepared. It is predicting good and giving good results.