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Moving averages, weighted moving averages, and exponential smoothing are three different types of forecasting methods that are capable of adapting to changes in the level of a horizontal pattern. Forecasting is primarily used to predict the type of approaching environment and prepare budgets to save on expenses to ultimately increase profits. Error measures give an improved probability percentage of the three different types of forecasting methods. Error measures with a lower measure of errors within moving averages weighted moving averages, and exponential smoothing measures are considered to be more accurate forecasting models. The primary error measures outlines were the mean absolute error (MAE), mean squared error (MSE) and mean absolute percentage error (MAPE). Through forecasting, the errors used can be used to calculate the forecasted data and compared to the actual data to improve forecasting techniques