The paper introduces the brms package, which allows R users to specify and fit a wide range of Bayesian single-level and multilevel models using the Stan probabilistic programming language. The package supports various response distributions and enables distributional regression, where all parameters of the response distribution can be predicted simultaneously. Non-linear relationships can be modeled using non-linear predictor terms or semi-parametric approaches like splines or Gaussian processes. The brms formula syntax extends the lme4 syntax, making it more flexible and powerful for specifying complex models. The paper provides an in-depth explanation of the syntax and demonstrates its utility through four examples: modeling fish catches, housing rents, insurance loss payments, and school children's performance. Each example highlights different aspects of the syntax and showcases the package's capabilities. The paper concludes by discussing future plans for extending the package and its potential applications in various scientific fields.The paper introduces the brms package, which allows R users to specify and fit a wide range of Bayesian single-level and multilevel models using the Stan probabilistic programming language. The package supports various response distributions and enables distributional regression, where all parameters of the response distribution can be predicted simultaneously. Non-linear relationships can be modeled using non-linear predictor terms or semi-parametric approaches like splines or Gaussian processes. The brms formula syntax extends the lme4 syntax, making it more flexible and powerful for specifying complex models. The paper provides an in-depth explanation of the syntax and demonstrates its utility through four examples: modeling fish catches, housing rents, insurance loss payments, and school children's performance. Each example highlights different aspects of the syntax and showcases the package's capabilities. The paper concludes by discussing future plans for extending the package and its potential applications in various scientific fields.