In the wake of weaker student enrollment, US colleges are struggling to fill their seats that is enough to generate revenue to balance their planned annual spending.  The interests are growing to forecast what students enrollment might be which never happened in the past.  Is it possible to forecast student enrollment?  Our short answer is yes, you can!  The next question is how accurate your prediction or forecasting will be.  In the world of econometrics and forecasting, there are two ways to predict any sort of predictions.  (1). Applying time series analyses and (2). Using some sort of econometric models.  There is also effort to combine these two approaches to come up with the lowest Mean Square Error (MSE).  Forecasting of student enrollment was rarely done in the past in decision making process.  The reason is simple.  In the past higher institutions do not need to do it due to strong demand for college education.  However, the condition has changed since then.  Rather than paying a lot of money to pay a consultant firm, an institution can just take the naive model i.e., take the average of enrollment over the period of analyses and available data.  This might be your best predictor for your (t+1) period of student enrollment.  Do not forget to consider the margin of error in your final judgment.  The more data one has, the closer the sample mean to its population average.  At least 30 observations are needed to satisfy the Central Limit Theorem.