Simple models can play pivotal roles in the quantification and framing of uncertainties surrounding climate change and sea-level rise. They are computationally efficient, transparent, and easier to reproduce. These qualities make simple models useful for uncertainty quantification and risk characterization. Simple model codes are increasingly distributed as open source, as well as actively shared and guided. Alas, computer codes used in the geosciences can often be hard to access, run, modify (e.g., with regards to assumptions and model components), and review. Here, we introduce a simple model framework for projections of global mean temperatures as well as regional sea levels and coastal flood risk (BRICK: Building blocks for Relevant Ice and Climate Knowledge). The BRICK model framework is written in R and Fortran and aims to help mitigate these issues, while maintaining a high degree of computational efficiency. We demonstrate the flexibility of this framework through simple model intercomparison experiments. Furthermore, we demonstrate that BRICK is suitable for risk assessment applications by using a didactic example in local flood risk management.