Globalized economic systems involve complex supply chains (SCs) where environmental and social impacts are to be managed in alignment with diverse stakeholder expectations and to mitigate sustainability-related risks. Quantitative modeling approaches for sustainable supply chain management (SSCM) have gained increasing attention. Compared to analytical models and mathematical programming , simulation methods in SSCM are underrepresented, although system dynamics (SD) modeling is suitable to simulate and examine complex and dynamic systems and to support long-term, strategic decision-making. This paper provides a review of SSCM-related SD models, systematizes SSCM from a systems thinking perspective in a conceptual framework, and proposes guidelines for SD modeling in SSCM research. A content analysis of related literature examines SD models for forward, reverse, and closed-loop SCs that include environmental or social aspects of sustainability . It is found that a majority of models deals with macroscopic levels of analysis while models for intra- and inter-organizational SCs are less prominent. SSCM-related SD models integrate environmental and social sustainability metrics, governmental pressures and incentives or customer expectations, but uncertainties and risks are seldom modeled. Inferences for future SD modeling in SSCM are derived from this review to address strengths and shortcomings of extant SD modeling approaches for SSCM. SSCM-related constructs, model validation and the need of hybrid models, which integrate different simulation, optimization, or multi-criteria decision-making models, are addressed. A framework for a systems thinking perspective on SSCM is conceptualized that may serve as a basis for future research.