Spatial and temporal variation in precipitation over varying seasons impacts multiple parameters. Examining the fluctuations and alterations in rainfall patterns across diverse spatial scales and the identification of trends in rainfall have been fundamental areas of interest in the varying fields globally. Trend analysis helps in comprehending past and current changes in climatic conditions, yet forecasting future scenarios is of immense value to decision-makers, enabling them to make informed decisions by considering anticipated variations in climate variables, such as Precipitation. Despite having various stochastic and statistical models, reliable rainfall forecasting remains a back-breaking issue. This study attempts to model and forecast SWM rainfall (June-September) for the Kutch district over the next 15 years. A five-year moving average of long-term IMD gauge station gridded annual rainfall data (0.25 × 0.25 degree) from 1961 to 2018 has been used. The ADF statistical test was applied to assess the stationarity of the series. A forecast using the univariate ARIMA (2,0,0) model indicates that there is a marked fall in SWM rainfall in upcoming years over the Kutch district, where the mean has fallen by −20.33%. The best fit ARIMA (p, d, q) model for sub-divisions; Abdasa (1,0,0), Anjar (2,0,2), Bhachau (4,0,0), Bhuj (2,0,2), Gandhidham (2,0,1), Lakhpat (5,0,0), Mandvi (2,0,2), Mundra (2,0,2), Nakhatrana (2,0,2) and Rapar (2,0,1). The mean (forecast) for all the Subdivisions has been reduced except Nakhatrana and Lakhpat have slightly increased by 0.60% and 0.29%, respectively.