{ "background": "Industrial machinery fleets are critical for economic development, yet systematic reliability assessments in West African operational contexts are scarce. Existing methodologies often fail to account for the hierarchical structure of fleet data and region-specific operational stressors.", "purpose and objectives": "This study aims to develop and apply a robust methodological framework for evaluating the reliability of industrial machinery fleets. The primary objective is to quantify the influence of multilevel factors—machine-level, operational, and environmental—on system failure rates.", "methodology": "A multilevel regression modelling approach was employed, analysing operational data from a heterogeneous fleet of heavy equipment. The core statistical model is a two-level hierarchical linear model: $\\lambda{ij} = \\beta{0j} + \\beta{1}X{1ij} + \\epsilon{ij}$, where $\\beta{0j} = \\gamma{00} + \\gamma{01}Z{j} + u{0j}$. Model parameters were estimated using restricted maximum likelihood with robust standard errors.", "findings": "The analysis revealed that environmental factors (notably airborne particulate concentration) exerted a stronger influence on reliability than machine age alone. A one-unit increase in particulate concentration was associated with a 15% increase in the hazard rate (95% CI: 11% to 19%). Operational maintenance practices at the depot level accounted for significant variance in intercepts.", "conclusion": "The proposed multilevel methodology provides a more nuanced and accurate assessment of fleet reliability than conventional single-level analyses. It successfully isolates the distinct contributions of nested factors prevalent in the studied context.", "recommendations": "Fleet managers should prioritise adaptive maintenance schedules responsive to real-time environmental data. Policymakers are advised to support the development of contextualised reliability benchmarks informed by hierarchical data structures.", "key words": "reliability engineering, multilevel modelling, fleet management, maintenance, industrial machinery, West Africa", "contribution statement": "This paper presents a novel application of hierarchical linear modelling to