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Aims To develop and validate a multifactorial risk model for predicting disease-free survival (DFS) in oral squamous cell carcinoma (OSCC) by integrating pathological features with systemic and tissue-based inflammatory markers.Methods In this retrospective multicentre study of 81 OSCC patients, systemic inflammatory blood markers and tissue-based spatial immune profiles (assessed via multiplex immunohistochemistry) were evaluated. Multivariate Cox regression analysis was performed to identify independent predictors of the primary outcome, DFS. A prognostic nomogram was constructed based on significant variables (p < 0.05), and model performance was evaluated using the concordance index (C-index).Results The final multifactorial model identified Stage 4b (adjusted HR (aHR)=10.68; p=0.003), high pre-treatment absolute neutrophil count (aHR=6.04; p=0.003) and high post-treatment lymphocyte-to-monocyte ratio (aHR=3.63; p<0.001) as significant systemic predictors. Within the tumour microenvironment, high CD68 +/CD3+ (aHR=3.60; p=0.006) and high CD66b−CD15+/CD68+ (aHR=2.68; p=0.013) ratios at the tumour centre (TC) were independent predictors of DFS. The integrated risk model achieved a C-index of 0.82, demonstrating superior predictive accuracy compared with traditional staging and other risk models.Conclusions The integration of systemic inflammatory markers and TC immune ratios with the pathological staging shows potential to enhance DFS prediction in OSCC. Pending future external validation, this multidimensional model may provide a useful framework for individualised risk stratification, potentially assisting in personalising post-treatment surveillance and adjuvant strategies for high-risk patients.