Life cycle inventories (LCI) of products and processes can be efficiently created using data from open literature combined with chemical engineering process heuristics. This endeavor requires a simple and reasonably accurate heuristic for each unit operation. We present a distillation model to determine reflux ratios and energy requirements, and compare the results to reflux ratios of real columns in the literature. Distillation is an energy intensive processing step in the chemical industry. It is the most common separation technique for miscible liquids and typically accounts for over half of the process heat requirements of a chemical manufacturing plant (Kunesh et al. 1995). Due to the large energies consumed, an accurate distillation heuristic is important for meaningful inventory calculations. Furthermore, determining the total energy requirement of a distillation column is more challenging than determining the energy of other important unit operations, such as reactors. The basic steps involved in modeling, designing, and optimizing distillation columns are well described in the literature. An economic trade-off of operating and capital costs leads to an economic optimum reflux ratio (Ropt). This optimum reflux is often reported to be 1.2 to 1.3 times the minimum reflux (Rm). Some situations, such as high energy costs, refrigeration, or high material costs cause deviations from this rule. Using the assumption that the actual reflux ratio (R) is a multiple of Rm, we use the following heuristic to determine the energy requirements of a distillation column: (1) Specify feed composition and condition as well as separation efficiency (2) Calculate Rm (3) Determine R from Rm and calculate energy required to condense the flow in the top of the column (4) Assume that energy in the reboiler replaces energy removed in the condenser and supplies specific heat requirements. The level of detail and accuracy in Rm calculations can vary greatly. The distillation model and the vapor liquid equilibrium data both add to the range of modeling choices. A very simple method is to correlate Rm with the boiling point difference of key components. Various short-cut methods and process simulators add complexity, but provide additional accuracy. When a life-cycle inventory is presented, many distillation columns are included. Therefore, transparency requires the model and calculations to be simple and easily verified and understood. Although many texts give the optimum reflux as a multiple of Rm, there are very few real operating columns that are well specified in the literature. The reflux ratios of all distillation columns found in the literature have been tabulated and compared to the values of Rm calculated with a short-cut (Underwood) method. A linear fit produced the ratio R = 1.5* Rm. We have incorporated this method with a simple vapor pressure model into our computational tool for determining LCI data.