This study investigated the user request evaluation tool's (URET) prediction sensitivity to weather forecast error. A quantitative experiment was designed and performed by the Federal Aviation Administration's Conflict Probe Assessment Team (CPAT) to evaluate the impact of weather forecast errors on URET trajectory and conflict predictions. The experiment used approximately two hours of traffic data recorded at the Indianapolis en route center in May 1999. The flights were time shifted to generate a sufficient number of test conflicts using a genetic algorithm technique developed by CPAT. The resulting scenario was input into the URET prototype system. To induce weather forecast error, the weather input file (rapid update cycle, RUC) was altered by adding 20 or 60 knots to the wind magnitude, 45 or 90 degrees to the wind direction, and 5 or 15 degrees Kelvin to the air temperature. This produced seven URET runs for the experiment -the unaltered control run and six treatment runs. The analysis compared the control run against the treatment runs. A methodology was developed to compare the trajectory and conflict prediction accuracy of these runs. A statistical analysis provided evidence that the forecast errors in wind magnitude and direction had significant effect on the longitudinal trajectory error and a modest impact on retracted false alerts, which caused at most an increase in the false alert probability by six percent. It also showed that the air temperature runs did not have a significant effect. Based on this experiment, a controller suspecting errors in the input wind forecast should expect only a modest impact on URET predictions. The impact would mainly be a moderate increase in the number of retractions of its conflict predictions (defined in this study as a retracted false alert). If the controller notices an increase in retractions, it may be symptomatic of inaccurate wind forecasts, which should be investigated.