Objectives: Outpatient parenteral antimicrobial therapy (OPAT) use has increased significantly as it provides safe and reliable administration of long-term antimicrobials for severe infections. Benefits of OPAT include fewer antibiotic or line-related complications, increased patient satisfaction, shorter hospitalizations, and lower costs. Although OPAT programs carefully screen patients for eligibility and safety prior to enrollment, complications can occur. There is a paucity of studies identifying predictors of clinical outcomes in OPAT patients. Here, we seek to identify baseline predictors of OPAT outcomes utilizing machine learning methodologies. Methods: We used electronic health record data from patients treated with OPAT between February 2019 and June 2022 at a large academic tertiary care hospital in Dallas, Texas. Three primary outcomes were examined: 1) clinical improvement at 30 days without evidence of reinfection; 2) patient actively being followed at 30 days; and 3) occurrence of any adverse event while on OPAT. Potential predictors were determined a priori, including demographic and clinical characteristics, OPAT setting, intravenous line type, and antimicrobials administered. Three classifiers were used to predict each outcome: logistic regression, random forest, and extreme gradient boosting (XGBoost). Model performance was measured using AUC, F1, and accuracy scores. Results: We included 664 unique patients in the study, of whom 57% were male. At 30 days, clinical improvement was present in 78% of patients. Two-thirds of patients (67%) were actively followed at 30 days, and 30% experienced an adverse event while on OPAT. The XGBoost model performed best for predicting treatment success (average AUC = 0.873), with significant predictors including ID consultation and the use of vancomycin. The logistic regression model was best for predicting adverse outcomes (average AUC = 0.710). Risk factors for adverse outcomes included management in the home setting and the use of vancomycin, daptomycin, or piperacillin-tazobactam. Conclusion: Outcomes of patients undergoing OPAT can be predicted with the use of easily-obtainable clinical and demographic factors. Patients requiring certain antimicrobial therapies, such as vancomycin or daptomycin, may derive less benefit from early hospital discharge and OPAT.