Sepsis is a serious health condition that is not well understood. It is defined as an overactive immune response that causes severe damage to healthy tissue, often resulting in death. Mathematical modeling has emerged as a useful tool to investigate key elements of the immune response and thus offers a useful method for studying sepsis. Here, a system of four ordinary differential equations is developed to simulate the dynamics of bacteria, the pro-inflammatory immune response, anti-inflammatory immune response, and tissue damage. The pro-inflammatory response is triggered by the presence of bacteria and leads to destruction of bacteria as well as damage to the tissue once the level of inflammation exceeds a certain threshold. The anti-inflammatory response works to temper the pro-inflammatory response, although it is not always capable of preventing sustained tissue damage. The model is used to assess the conditions under which health, aseptic (inflammation-driven) death, or septic (bacteria-driven) death is predicted in both the presence and absence of an induced E. Coli bacterial infection in rats. Model parameters are fit to experimental data from rat sepsis studies. The model is used to predict the survivability range for an infection while varying the initial amount, growth rate, or virulence of the bacteria in the system.