diff --git a/CITATION.cff b/CITATION.cff
new file mode 100644
index 000000000..d783a5a36
--- /dev/null
+++ b/CITATION.cff
@@ -0,0 +1,11 @@
+cff-version: 1.2.0
+message: "If you use this software, please it as below."
+authors:
+- family-names: "Bosch"
+  given-names: "Nathanael"
+  orcid: "https://orcid.org/0000-0003-0139-4622"
+title: 'ProbNumDiffEq.jl: Probabilistic Numerical Solvers for Ordinary Differential Equations in Julia'
+version: 0.16.2
+doi: 10.21105/joss.07048
+date-released: '2024-10-01'
+url: https://doi.org/10.21105/joss.07048
\ No newline at end of file
diff --git a/README.md b/README.md
index 401d09eda..83c056dd8 100644
--- a/README.md
+++ b/README.md
@@ -5,6 +5,7 @@
 [![Build Status](https://github.com/nathanaelbosch/ProbNumDiffEq.jl/workflows/CI/badge.svg)](https://github.com/nathanaelbosch/ProbNumDiffEq.jl/actions)
 [![Coverage](https://codecov.io/gh/nathanaelbosch/ProbNumDiffEq.jl/branch/main/graph/badge.svg?token=eufIemCGXn)](https://codecov.io/gh/nathanaelbosch/ProbNumDiffEq.jl)
 [![Benchmarks](http://img.shields.io/badge/benchmarks-docs-blueviolet.svg)](https://nathanaelbosch.github.io/ProbNumDiffEq.jl/dev/benchmarks/multi-language-wrappers/)
+[![DOI](https://joss.theoj.org/papers/10.21105/joss.07048/status.svg)](https://doi.org/10.21105/joss.07048)
 
 ![Banner](./examples/banner.svg?raw=true)
 
@@ -75,6 +76,26 @@ If there is anything that's unclear or doesn't work, we would very much like to
 This includes not just bugs and feature requests but also general questions about the software, feedback and suggestions.
 
 
+## Citing ProbNumDiffEq.jl
+
+If you use ProbNumDiffEq.jl helpful for your research project, please cite our JOSS paper ([link](https://doi.org/10.21105/joss.07048)):
+```
+@article{Bosch2024,
+  doi =          {10.21105/joss.07048},
+  url =          {https://doi.org/10.21105/joss.07048},
+  year =         2024,
+  publisher =    {The Open Journal},
+  volume =       9,
+  number =       101,
+  pages =        7048,
+  author =       {Nathanael Bosch},
+  title =        {ProbNumDiffEq.jl: Probabilistic Numerical Solvers for Ordinary
+                  Differential Equations in Julia},
+  journal =      {Journal of Open Source Software}
+}
+```
+
+
 ## Related packages
 
 - [ProbDiffEq](https://pnkraemer.github.io/probdiffeq/) is similar in scope to ProbNumDiffEq.jl and it provides fast and feature-rich probabilistic ODE solvers but is implemented in Python and built on JAX.