The 45th Weather Squadron (45 WS) forecasters at Cape Canaveral Air Force Station (CCAFS) in Florida include a probability of thunderstorm occurrence in their daily 24-hour and weekly planning forecasts. This information is used for general scheduling of operations at CCAFS and Kennedy Space Center (KSC). These facilities are located in east-central Florida at the east end of a corridor known as ‘Lightning Alley’, an indication that lightning has a large impact on spacelift operations. Much of the current lightning probability forecast is based on a subjective analysis of model and observational data. The forecasters requested that a new lightning probability forecast tool based on statistical analysis of historical warm-season (May-September) data be developed in order to increase the objectivity of the daily thunderstorm probability forecast. The tool is a set of statistical lightning forecast equations that provide a lightning occurrence probability for the day by 1100 UTC (0700 EDT) during the warm season. This study used 15 years (1989-2003) of warm season data to develop the objective forecast equations. The local and peninsula-wide soundings were used to calculate stability parameters and flow regimes for equation predictors. Data from the Cloud-to-Ground Lightning Surveillance System (CGLSS), a local network of cloud-to-ground lightning sensors, were used to determine lightning occurrence for each day. The CGLSS data have been found to be more reliable indicators of lightning in the area than surface observations through local informal analyses. This work was based on the results from two earlier research projects. Everitt (1999) used surface observations and rawinsonde data to develop logistic regression equations that forecast the daily thunderstorm probability at CCAFS. The Everitt (1999) equations showed an improvement in skill over the Neumann-Pfeffer thunderstorm index (Neumann 1971), which was developed specifically for the KSC/CCAFS area. Lericos et al. (2002) developed lightning distributions over the Florida peninsula that were stratified by flow regimes. The flow regimes were inferred from the average wind direction in the 1000-700 mb layer at Miami (MIA), Tampa (TBW), and Jacksonville (JAX), Florida, and the lightning data were from the National Lightning Detection Network. The results suggested that the daily flow regime may be an important predictor of lightning occurrence on KSC/CCAFS. The 1200 UTC MIA, TBW, and JAX soundings were used in this study as in Lericos et al. (2002) to calculate the daily flow regimes during the period of record. Going a step further, the probabilities of lightning occurrence based on the flow regimes were calculated using data from CGLSS. Other papers on CGLSS and use of its archived data have been submitted to this conference. These probabilities were also used as predictors in the statistical lightning forecast equations, but they were found to improve the thunderstorm forecast over persistence and climatology when used on their own. The equations were developed using the logistic regression method, as in Everitt (1999), which is the appropriate statistical technique when trying to forecast probabilities from binary predictors as in this case when lightning occurred (1) or not (0). The presentation will demonstrate the equation development, show the equations and their predictors, and describe the equation performance. It will also discuss the flow regime lightning probabilities by month and their improvement in skill over persistence and climatology.