In this particular case, future predictability doesn't work. The sample size is way too small (as SCOTUS only hears ~80 cases/year), and the cases are not evenly distributed. The last couple years, for example, the court has become very conservative and happens to hear a significantly higher percentage of business-related cases. It's hard to predict anything from that.
It would make more sense to divide the data into training and validation/cross-validation data sets like in a standard machine learning approach.