Darragh, IAJ, Egan, B, Nolan, D, and Bennett, KE. Predicting a successful attempt in raw powerlifting. A nonlinear mixed logistic regression analysis. J Strength Cond Res XX(X): 000-000, 2025-This study aimed to predict successful lift attempts in raw powerlifting by examining the influence of jump size (the absolute difference in weight between consecutive attempts) and other factors, using a logistic regression model with nonlinear splines. Data from 93,333 lifters (62,679 males, 30,654 females) across 6,979 International Powerlifting Federation competitions were analyzed. The data set was partitioned into training (80%) and test (20%) sets, with sex-specific models developed to account for class imbalance. Predictors included jump size, lift type (squat, bench press, deadlift), attempt transition (first-to-second or second-to-third), and covariates such as body mass, age, and opening attempt weight. Random effects for lifter identity were included to control for individual performance variability. Significance was set at p 20 kg, especially on third attempts. Bench press success increased slightly with jump sizes 10 kg significantly reduced success, particularly on third attempts. In the bench press, female lifters showed an almost linear decline in success with increasing jump size on second attempts, with third-attempt success decreasing sharply beyond 4 kg. Female deadlift success followed a similar pattern to squats but showed slightly greater tolerance, with optimal jumps approximately 9-11 kg. In both sexes, third attempts consistently had lower success rates than second attempts. These findings highlight the nuanced role of jump size in attempt success and provide actionable insights for competition strategy. Coaches and lifters can use these results to optimize attempt selection, particularly in balancing risk and reward across attempts.