The ensuing research aims at estimating the future market size of domestic Indian apparel industry. The study is based on secondary data and uses longitudinal study design. Univariate time series data is used in this study and annual retail sales data, collected from reliable secondary sources, for the period 2000 to 2019 forms the basis of generating predictive models. Owing to the available number of observations in the dataset, the researchers have considered Holt's exponential smoothing

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... od for the purpose of model generation and making forecasts. The absence of seasonal component in the time series data suggests the use of double exponential smoothing technique which includes effects of trend only. The analysis begins with the forecast of nineteen years with various combination of the coefficients, namely, α and β values and then deviation computed from the actual data. The deviation or the error estimates, namely MSE, MAPE, and MAD have been used to identify the best model in the present research study. The paper concludes with the actual forecasts for the next three years, 2020 till 2022 using the best model, i.e. the model which has resulted in minimum error. To the best of the knowledge of the researchers, this present study makes a maiden attempt to use Holt's method at an individual level to predict the future market size of the second largest retail industry in India. Apart from the scholarly contribution, the researchers anticipate this study outcome likely to act as an aid to the apparel marketers for their future planning.