A New Method for an Objective Measurement of the Judicial Workload – the Application of a Prediction Model Based on an Algorithm Formed by Multiple Linear Regression in Court Administration

Abstract

The timeliness of judgments is mostly influenced by the workload of judges, which, in addition to the number of court cases, to a large extent depends on the amount of judicial working time necessary to resolve them, i.e. their complexity. Regarding the latter, there are significant differences among each of the cases, and the territorial distribution of cases of different complexity is not even. Therefore, in order to measure the judicial workload reliably, to distribute it fairly, and to ensure timeliness, it is also essential to take into account the complexity of court cases. The question is: How is this possible? My retrospective empirical studies on the records of resolved first instance criminal court cases have proved that the amount of judicial working time demand, to conclude cases as a dependent variable, is related to certain substantive and procedural attributes of the case file, as independent variables. Therefore, a prediction model based on an algorithm created by multiple linear regression can be constructed. The amount of judicial working time demand to conclude a given case, can be reliably estimated with it in advance, when a case is submitted and a weighting can be assigned to the case, expressing its complexity with reasonable accuracy. Thus, a system for measuring and allocating the workload of judges can be developed after appropriate adaptation, and it can take into account the differences in the complexity of individual cases more accurately, than currently used methods, and which can be applied independently of the jurisdiction, court, legal system and judicial system.