The global ubiquity and demonstrated toxicity of microplastics has led governments around the world to express the need for a risk assessment on microplastics. To conduct a risk assessment, scientists often draw upon frameworks from other contaminants, however we argue that microplastics are a unique pollutant and thus require a unique framework. Microplastics are a multidimensional contaminant, differing in size, shape, polymer type, and chemical cocktail. Each of these dimensions may influence the toxicity of the particle. Furthermore, microplastic pollution exists as a complex and dynamic mixture of particles, that varies over temporal and spatial scales. Thus, we propose a multidimensional risk framework for microplastics that incorporates, rather than simplifies, the multidimensionality of the contaminant as well as the contaminant mixture. With this framework, we can calculate a particle-specific hazard value that describes the potential for a single particle to cause harm based on its chemical and physical properties. The particle-specific hazard values can then be combined based on the number and type of particles in an environmental sample to inform the overall hazard value of the sample. The risk of the sample can then be calculated, which is dependent on the overall hazard value and the concentration of particles in the sample. Risk values among samples in the environment can be compared to illustrate differences among locations or seasons, or can be placed in a management framework with thresholds to guide regulatory decisions. To demonstrate the utility of our proposed framework, we perform a case study using data from San Francisco Bay. Our proposed framework is just that, and requires new research for application. To strengthen the ability of this framework to accurately predict risk, we propose a testing scheme that prioritizes strategic experimental designs that will increase our understanding of how each dimension of microplastics affect the toxicity (or hazard value) of a particle.