Perspectives on Judicial Efficiency: Case Study of Predictive Modeling in Kenyan High Courts

Persistent case backlogs and delays in providing timely justice undermine judicial efficiency and impose significant societal costs through legal expenditure, incentives for vexatious litigation, weakened rule of law, and erosion of public trust. In Kenya, quantitative analysis examining factors influencing resolution timelines within the High Court system has been limited. This study addresses this critical knowledge gap by applying survival analysis techniques to a comprehensive dataset spanning over 90,000 cases from 2012–2022. Specifically, this is aimed to perform explanatory data analysis of factors influencing the survival time of cases in Kenyan High Courts; to predict the time for a case to be determined in Kenyan High Courts using survival models; and to compare the model precision between Cox regression and other parametric survival models. This study applied exploratory visualization and regression modeling, where key predictors of case duration were identified, and the performance of parametric and semi-parametric survival models were fitted to establish comparison. Exploratory investigation indicated that family cases exhibited the longest durations, whereas criminal cases and anti-corruption cases were resolved the quickest. Appealed cases generally had a longer duration as well. According to the Akaike Information Criterion, the parametric Weibull distribution provided a better fit for the complicated event history data than the semi-parametric Cox Proportional Hazards model. Weibull regression showed civil, constitutional, family, and appeal cases had considerably lower resolution risks than anti-corruption proceedings. While certain case types may have counterintuitive estimates, this analysis provides a robust quantitative framework for resource allocation, legislation, and initiatives to reduce disproportionate backlogs across litigation areas and uphold constitutional rights to timely justice, which is critical for economic growth and societal prosperity.

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Publication Details

Journal
International Journal for Court Administration
Published
2025-01-01
DOI
https://doi.org/10.36745/ijca.627
Primary Topic
Artificial Intelligence in Law
Type
article
Field-Weighted Citation Impact
0.00

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article

Perspectives on Judicial Efficiency: Case Study of Predictive Modeling in Kenyan High Courts

Alex Kangogo Kandie, Edwine Benson Atitwa, Wesley Nyaluke
International Journal for Court Administration
Artificial Intelligence in Law
article

Perspectives on Judicial Efficiency: Case Study of Predictive Modeling in Kenyan High Courts

Alex Kangogo Kandie, Edwine Benson Atitwa, Wesley Nyaluke
article en

Abstract

Persistent case backlogs and delays in providing timely justice undermine judicial efficiency and impose significant societal costs through legal expenditure, incentives for vexatious litigation, weakened rule of law, and erosion of public trust. In Kenya, quantitative analysis examining factors influencing resolution timelines within the High Court system has been limited. This study addresses this critical knowledge gap by applying survival analysis techniques to a comprehensive dataset spanning over 90,000 cases from 2012–2022. Specifically, this is aimed to perform explanatory data analysis of factors influencing the survival time of cases in Kenyan High Courts; to predict the time for a case to be determined in Kenyan High Courts using survival models; and to compare the model precision between Cox regression and other parametric survival models. This study applied exploratory visualization and regression modeling, where key predictors of case duration were identified, and the performance of parametric and semi-parametric survival models were fitted to establish comparison. Exploratory investigation indicated that family cases exhibited the longest durations, whereas criminal cases and anti-corruption cases were resolved the quickest. Appealed cases generally had a longer duration as well. According to the Akaike Information Criterion, the parametric Weibull distribution provided a better fit for the complicated event history data than the semi-parametric Cox Proportional Hazards model. Weibull regression showed civil, constitutional, family, and appeal cases had considerably lower resolution risks than anti-corruption proceedings. While certain case types may have counterintuitive estimates, this analysis provides a robust quantitative framework for resource allocation, legislation, and initiatives to reduce disproportionate backlogs across litigation areas and uphold constitutional rights to timely justice, which is critical for economic growth and societal prosperity.

International Journal for Court AdministrationVol. 16(2)
University of Embu
Openalex Percentile: Top 67%
Artificial Intelligence in Law
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Perspectives on Judicial Efficiency: Case Study of Predictive Modeling in Kenyan High Courts — Alex Kangogo Kandie, Edwine Benson Atitwa, et al. · International Journal for Court Administration (2025) | TGRS Research Map | TGRS