Ten years (19972006) of summer (JuneAugust) daytime (14000000 UTC) Weather Surveillance Radar-1988 Doppler data for Houston, Texas, were examined to determine the best radar-derived predictors of the first cloud-to-ground lightning flash from a convective cell. Convective cells were tracked using a modified version of the Storm Cell Identification and Tracking (SCIT) algorithm and then correlated to cloud-to-ground lightning data from the National Lightning Detection Network (NLDN). Combinations of three radar reflectivity values (30, 35, and 40 dBZ) at four isothermal levels (10, 15, 20, and updraft 10C) and a new radar-derived product, vertically integrated ice (VII), were used to optimize a radar-based lightning forecast algorithm. Forecasts were also delineated by range and the number of times a cell was identified and tracked by the modified SCIT algorithm. This study objectively analyzed 67 384 unique cells and 1 028 510 lightning flashes to find the best lightning forecast criteria. Results show that using 30 dBZ at the 15 or 20C isotherm on cells within 75 km of the radar that have been tracked for at least two consecutive scans produces the best lightning forecasts with a critical success index (CSI) of 0.68. The best VII predictor values were 0.42 or 0.58 kg m2 on cells within 75 km of the radar that have been tracked for at least two consecutive scans, producing a CSI of 0.67. Lead times for these predictors were 10.0 and 13.4 min, respectively. Lead times greater than 10 min occurred with less stringent predictors (e.g., 30 dBZ at 10C or VII greater than 0.25 kg m2 on cells within 125 km with a minimum track count of 2), but lower CSI values result. In general, cells tracked for multiple scans provide higher CSIs and lead times than decreasing the range from the radar or changing the reflectivity threshold and height.