Attorneys are key players in the U.S. Supreme Court decision-making process who use their legal arguments to influence the justices' decisions. Tasked with preparing merits briefs that make initial forays into the legal issues in a case, attorneys use that space to limit the range of possible outcomes and direct the justices' focus toward certain (favorable) areas of the law. Yet scholars understand very little about this process because they have struggled to empirically identify and examine legal arguments and their impact on the Court's decisions. In response to this problem, I use a combination of human-assisted coding and machine learning techniques to develop a method of extracting the core components of a legal argument for analysis. Using data collected from the legal arguments in more than three thousand briefs from 1,509 different cases the Court reviewed between the 1984 and 2007 terms, I study attorneys' use of the law, focusing on their decision to frame their arguments using prevailing case law or a wholly new, entrepreneurial argument. I show that attorneys' decisions regarding the framing of their arguments - whether to align their argument with the Court's prevailing approach or to use an entrepreneurial argument to radically change an area of case law - can alter the justices' decisions in a case. I use that same data to show that attorneys are strategic in their deployment of these frames, looking for signs the justices might respond positively to one type over the other if the argument is made well.
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