Research interests in feral hogs typically involve their negative impacts on ecosystems or their potential as a disease reservoir, especially with disease transmission to domestic swine. Authors within scientific literature state that feral hogs were captured as part of their research, but usually fail to mention specific conditions in which hogs were captured. Novice researchers of feral hogs must rely on ‘word-of-mouth’ to acquire this information or learn it by trial and error. Our objective was to place this knowledge into the scientific literature as an aid to future researchers of feral hogs. Feral hogs were captured in box traps or corral-style traps baited with sour corn in eastern and southern Texas during April 2004 - June 2005. Daily weather conditions (i.e., high and low temperatures, humidity, average wind speed, and precipitation) were obtained from the nearest weather station for each trapping location. A predictive model using logistic regression was developed from data collected in eastern Texas to predict the success of feral hog trapping on a given night based on significant weather variables and then tested on data collected from southern Texas. A successful night of trapping was defined as ≥1 hog being captured. A total of 212 feral hogs were captured during 166 nights of trapping (1,558 trap-nights). The threshold of 22°C for the daily minimum temperature was the only significant (Chi-square = 26.5, df = 1, P < 0.0001) weather variable found. The majority of hogs (97%) were captured when the daily minimum temperature was below 22°C. The model could correctly predict (95%) when trapping success of feral hogs was unlikely (daily minimum temperature ≥22°C), but it was less accurate (50%) in predicting the success of feral hog trapping when the daily minimum temperatures were <22°C. Because the majority of feral hogs live in areas with hot, humid climates during the summer (i.e., southeastern United States), trapping success, especially during July and August, would be unlikely. Research schedules and budgets should be planned to avoid such periods of extreme heat.