Predicting the trend of non-seasonal data is a difficult task in Social Science. In this research work, we used time series analysis of 144 observations on monthly basis for record of reported cases of tuberculosis patients in Minna General Hospital, Niger State from the period of 2007-2018. Exploratory Data Analysis (EDA: Time Plot and Descriptive Statistics), Stationarity Test (ADF), Trend estimation (<i><span style="font-family:Verdana;">T</span><sub><span style="font-family:Verdana;">t</span></sub></i><span style="font-family:Verdana;">), Normality Test, and Forecast evaluation were carried out. The Augmented Dickey Fuller test for stationarity was conducted and the result revealed that the series are not stationary but became stationary after first difference. The correlogram established that the ARIMA (2, 1, 3) was the best model this was further confirmed from the result of L-jung Box. Equation for ARIMA (2, 1, 3) was given as </span><i><span style="font-family:Verdana;">X</span><sub><span style="font-family:Verdana;">t</span></sub></i><span style="font-family:Verdana;"> + 0.6867</span><i><span style="font-family:Verdana;">X</span><sub><span style="font-family:Verdana;">t-</span></sub></i><sub><span style="font-family:Verdana;">1</span></sub><span style="font-family:Verdana;"> – 0.8859</span><i><span style="font-family:Verdana;">X</span><sub><span style="font-family:Verdana;">t-</span></sub></i><sub><span style="font-family:Verdana;">2</span></sub><span style="font-family:Verdana;"> = </span><i><span style="font-family:Verdana;">E</span><sub><span style="font-family:Verdana;">t</span></sub></i><span style="font-family:Verdana;"> + 1.3077</span><i><span style="font-family:Verdana;">E</span><sub><span style="font-family:Verdana;">t-</span></sub></i><sub><span style="font-family:Verdana;">1</span></sub> -<span><span><span style="font-family:;" "=""><span><span style="font-family:Verdana;"> 1.2328</span><i><span style="font-family:Verdana;">E</span><sub><span style="font-family:Verdana;">t-</span></sub></i><