diff --git a/README.md b/README.md
index e1c8400..3db71e2 100644
--- a/README.md
+++ b/README.md
@@ -5,7 +5,7 @@
 ![Gitea Release](https://img.shields.io/gitea/v/release/rmontanana/bayesnet?gitea_url=https://gitea.rmontanana.es:3000)
 [![Codacy Badge](https://app.codacy.com/project/badge/Grade/cf3e0ac71d764650b1bf4d8d00d303b1)](https://app.codacy.com/gh/Doctorado-ML/BayesNet/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)
 ![Gitea Last Commit](https://img.shields.io/gitea/last-commit/rmontanana/bayesnet?gitea_url=https://gitea.rmontanana.es:3000&logo=gitea)
-![Static Badge](https://img.shields.io/badge/Coverage-97,1%25-green)
+![Static Badge](https://img.shields.io/badge/Coverage-97,2%25-green)
 
 Bayesian Network Classifiers using libtorch from scratch
 
diff --git a/tests/TestBayesClassifier.cc b/tests/TestBayesClassifier.cc
index 729f01e..9b2bb85 100644
--- a/tests/TestBayesClassifier.cc
+++ b/tests/TestBayesClassifier.cc
@@ -79,6 +79,14 @@ TEST_CASE("Topological order", "[Classifier]")
     REQUIRE(order[2] == "sepalwidth");
     REQUIRE(order[3] == "petalwidth");
 }
+TEST_CASE("Dump_cpt", "[Classifier]")
+{
+    auto model = bayesnet::TAN();
+    auto raw = RawDatasets("iris", true);
+    model.fit(raw.Xt, raw.yt, raw.featurest, raw.classNamet, raw.statest);
+    auto cpt = model.dump_cpt();
+    REQUIRE(cpt.size() == 1713);
+}
 TEST_CASE("Not fitted model", "[Classifier]")
 {
     auto model = bayesnet::TAN();