<p>Hemodialysis machine reliability directly affects treatment continuity and patient safety, yet real-world analyses of operational failures remain limited, particularly in resource-constrained healthcare systems. This study presents a multi-hospital sentinel case study demonstrating an integrated reliability assessment framework for hemodialysis machines using retrospective maintenance records from a geographically distributed sample of 14 machines operating across twelve hospitals in six Syrian governorates. Twenty-eight component-level failure modes were identified over one year of operation. The proposed workflow combined mean time between failures (MTBF), short-term failure probability estimation, Weibull survival modeling, regression analysis, and unsupervised clustering to characterize component behavior and stratify operational risk. The analysis revealed heterogeneous reliability patterns across subsystems. A high-risk cluster—including the heater, temperature sensor, bicarbonate concentrate metering and mixing pump, pressure sensor, and intravenous sensor—showed relatively short MTBF values and recurrent failures across multiple machines. Weibull analysis identified distinct hazard signatures, with several sensors and pumps exhibiting early-life fragility (k &lt; 1). Failure recurrence alone did not significantly predict MTBF (<i>p</i> = 0.16), indicating that frequency-based metrics incompletely capture degradation behavior. Although based on a limited sample and observation period, this case study demonstrates how heterogeneous maintenance logs can be transformed into a unified reliability and risk-mapping framework capable of supporting preventive maintenance planning and operational decision-making in dialysis units.</p>