Recent studies reveal many Americans are sedentary. Although the public is aware of the importance of exercise, few studies focus on the role or development of appropriate fitness goals for adults. Quite often, aerobic fitness goals are unrealistic and unattainable for adults. Few fitness professionals use individual data when establishing fitness goals for adults. The 1.5 mile run is a well-established field test commonly used for estimating aerobic fitness (capacity). The purpose of this study was to utilize regression analysis to develop a model for estimating individualized 1.5 mile run times for adults and then cross-validate the model to determine it's accuracy. There were 259 participants in the validation group. Physical characteristics (mean±sd) of these 114 males and 145 females were: age 25.2±8.5 yr, 24.5±7.3 yr; percent fat 15.9±6.0%, 24.4±5.8%; 1.5 mile time 11.3±1.8 min, 14.3±2.4 min, respectively. The cross-validation group contained 83 males and 108 females and their physical characteristics were: age 23.4±5.7 yr, 25.2±8.5 yr; percent fat 12.9±5.3%, 23.0±5.4%; 1.5 mile time 10.3±1.4 min, 13.8±2.1 min, respectively. Participants had their skinfold measures taken (males-chest, abdomen, thigh: females-tricep, suprailiac, thigh) and then participated in a 14 week training program. At the conclusion of the training program, each participant completed a 1.5 mile run. This data was utilized in the regression analysis. The first step in the regression analysis was to enter age and the sum of three skinfolds (S3) into a multiple regression model followed by gender (females=0, males=1). Homogeneity of regression slope and intercept was then performed to determine if a single model could be used for men and women. The accuracy of the derived model was determined on the cross-validation group from the following standard error of estimate (SEE) equations: SEE1=sy÷1-r2yy' and SEE2=÷(S(y-y')2)/(n-1). Results of the regression analysis revealed that age and sum of skinfolds were each significant (p<.05) predictors of 1.5 mile run times. Homogeneity of regression slope and intercept revealed a common slope (p>.05) and different intercepts (p<.05). The final derived model: 9.816 + (age*0.052) + (S3*0.050) - (gender[0,1]*2.641) was found to be accurate (SEE1=1.49 min, SEE2=1.52 min) for estimating 1.5 mile run times. In conclusion, results of this study revealed the derived model is accurate for estimating 1.5 mile run times in healthy adults. These run times may be used with adults beginning an aerobic fitness program for goal-setting standards.