Screening for public safety positions (e.g., police officers, fire fighters, military service members) is a difficult and challenging task. Notably, the military has been widely criticized because of the general lack of an empirically based system or program for mental health screening. The purpose of the present study is to describe the use of statistical prediction rules for this task. Prediction rules were derived and validated using U.S. Air Force (USAF) recruits in basic military training (N = 50,322). Items from the Lackland Behavioral Questionnaire were used as predictors. General attrition (discharge for any reason before completing term of service) and disciplinary offenses (including criminal charges) were used as outcomes. For trainees in the top 2% or 1% of the general attrition prediction rule, 63% and 68% were discharged before they completed their first 4 years. The base rate was 25%. Similarly, for trainees in the top 2% or 1% of the disciplinary offenses prediction rule, 35% and 39% had a significant disciplinary offense over the following 4 years. The base rate was 15.5%. The results suggest that we may be able to use biographical data inventories and statistical prediction rules to identify a small percentage of trainees in public safety fields with significant mental health or behavioral histories who are at elevated risk for general attrition and disciplinary offenses.