Background <p>Acute compartment syndrome (ACS) following lower extremity arterial injuries necessitates urgent fasciotomy to prevent limb loss, yet current diagnostic tools lack specificity for ischemia–reperfusion pathophysiology. Our study aimed to develop a nomogram combining biomarkers and clinical indicators to predict fasciotomy risk, enhancing early risk stratification and optimizing surgical decision-making.</p> Materials and methods <p>In this retrospective case–control study (2010–2024), data were sourced from a tertiary hospital in China. A total of 146 patients with traumatic femoral or popliteal artery injuries were stratified into fasciotomy (<i>n</i> = 45) and non-fasciotomy (<i>n</i> = 101) groups. Adhering to the events-per-variable (EPV) principle (10:1), predictors were selected via least absolute shrinkage and selection operator (LASSO) regression and bootstrap validation. A multivariable logistic regression model was internally validated using tenfold cross-validation and 1000 bootstrap replicates.</p> Results <p>Four independent predictors were retained: limb ischemia severity (odds ratio [OR] = 4.25, 95% confidence interval [CI]: 1.97–10.02), K⁺ (OR = 6.99, 95% CI: 2.60–21.73), creatine kinase (CK; OR = 1.18, 95% CI: 1.08–1.30), and neutrophils (NEU) with a nonlinear threshold effect (OR = 1.20, 95% CI: 1.10–1.33). The nomogram demonstrated excellent discrimination (area under the curve [AUC] = 0.877, 95% CI: 0.819–0.934), precise calibration (Hosmer–Lemeshow <i>P</i> = 0.417), and broad clinical utility (net benefit threshold: 3–87%).</p> Conclusions <p>This study integrated accessible clinical and laboratory data and identified limb ischemia severity, K⁺, CK, and NEU as factors associated with fasciotomy risk. A nomogram based on these variables demonstrated reliable predictive performance and strong clinical applicability, enabling timely risk assessment and early intervention in patients with lower extremity arterial injuries.</p> Level of evidence <p>Level 4.</p>