The world is now facing the possibility a highly pathogenic H5N1 influenza A virus might gain the capability of human-to-human transmission, causing a pandemic. If there is an outbreak, lowering the maximum prevalence of the pandemic by social-distancing measures will help by reducing the demand for scarce resources of respiratory support and releasing pressure from the public health system. We used a differential equations based compartment model to investigate the measure of school closure. This model is similar in form to differential rate laws of chemical kinetics based on analogous principles of mass action. A Susceptible/Exposed/Infected/Recovered/Cross-Immune (SEIRC) model has been constructed and run on different scenarios to predict the effectiveness of school closure during an influenza pandemic in Kirksville, MO, a rural town with population of about 17,000. For a basic reproduction number (R₀) of 1.6 (R₀ is the average number of secondary infections caused by a single typical infected individual among a completely susceptible population.), the results show that temporary closure of schools and colleges may be able to lower the prevalence at the peak of the pandemic from 312 to 36 cases(i.e., by about 88 percent). With a higher R₀ of 4.0, results showed maximum prevalence reduced by about 71 percent (from 2900 to 850 cases). Future study will divide the Kirksville population into more detailed subclasses to look closely at the effect of variation in contact rates among members of different groups.