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While circuit court judges may strive to be neutral interpreters of the law, theories of judicial behavior argue more than just the law impacts judicial decision-making. Scholars have explored the influence of a judge’s unique individual personality on their behavior and its inevitable impact on law and policy within the United States. While these studies have focused exclusively on the U.S. Supreme Court, the vast majority of appellate decisions within the U.S. are made by circuit judges and the influence of these judges’ personalities is crucial in furthering our understanding of circuit judicial decision-making. Further, the rotating nature of circuit judge panels allows for a unique opportunity to examine personality and judicial behavior not seen at the Supreme Court. To determine the impact of personality at the circuit level, I collect a novel dataset of over 56,000 pre-nomination texts – such as speeches, judicial opinions, and academic article - for 200 circuit court judges confirmed since 1987. Next, I use machine learning to generate the first personality trait estimates for individual U.S. circuit court judges. These estimates are then used to analyze the impact of personality across several elements of judicial behavior such as compliance with the Supreme Court, dissenting behavior, and panel effects. Personality dramatically impacts various aspects of judicial behavior, such as judges low in agreeableness being more likely to dissent in a case while those high in conscientiousness are more likely to adhere to Supreme Court precedent. In doing so, this project further develops our understandings of judicial decision-making while simultaneously providing two novel data contributions: a repository of pre-nomination circuit judge texts and the first personality trait estimates for circuit court judges.