This study rigorously analyzes the application and trends of capital punishment in the United States from 1976 to 2016, employing comprehensive datasets that illuminate historical patterns and contemporary challenges. The dataset includes information from each state’s Department of Corrections and the NAACP Legal Defense Fund. By integrating decision trees and logistic regression models, we explore significant racial and gender disparities in the imposition of the death penalty, highlighting fairness and impartiality concerns in capital sentencing. Our findings demonstrate a persistent overrepresentation of certain racial groups within death row populations, with racial biases evidently influencing sentencing outcomes. We reveal that lethal injection, as the predominant execution method, reflects a shift toward methods perceived as more humane, though the ethical debates surrounding capital punishment remain contentious. The regional analysis suggests that geographical factors play a crucial role in the administration of justice, particularly in the South, which exhibits a pronounced inclination toward the death penalty. Furthermore, our predictive models showcase the potential of machine learning in forecasting trends and outcomes within judicial data, offering novel approaches to understanding and reforming capital sentencing practices. This research contributes to ongoing dialogues by providing empirical insights that underscore the need for comprehensive reforms to achieve a more equitable justice system.