diff --git a/ddtrace/llmobs/_llmobs.py b/ddtrace/llmobs/_llmobs.py
index 75d1b15761a..94a5e421975 100644
--- a/ddtrace/llmobs/_llmobs.py
+++ b/ddtrace/llmobs/_llmobs.py
@@ -1713,6 +1713,10 @@ def submit_evaluation(
                 error = "invalid_metric_label"
                 raise ValueError("label must be the specified name of the evaluation metric.")
 
+            if "." in label:
+                error = "invalid_label_value"
+                raise ValueError("label value must not contain a '.'.")
+
             metric_type = metric_type.lower()
             if metric_type not in ("categorical", "score", "boolean"):
                 error = "invalid_metric_type"
diff --git a/releasenotes/notes/fix-prevent-dots-in-evaluation-metric-labels-ab5caab19d52d3e1.yaml b/releasenotes/notes/fix-prevent-dots-in-evaluation-metric-labels-ab5caab19d52d3e1.yaml
new file mode 100644
index 00000000000..aa05c28cc21
--- /dev/null
+++ b/releasenotes/notes/fix-prevent-dots-in-evaluation-metric-labels-ab5caab19d52d3e1.yaml
@@ -0,0 +1,4 @@
+fixes:
+  - |
+    LLM Observability: This fix resolves an issue where evaluation-metric labels containing dots could be interpreted as nested objects by adding validation that rejects such labels and provides a clear error message instructing users to use alternative naming conventions.
+
diff --git a/tests/llmobs/test_llmobs_service.py b/tests/llmobs/test_llmobs_service.py
index ccd70167fb7..da6f419faf9 100644
--- a/tests/llmobs/test_llmobs_service.py
+++ b/tests/llmobs/test_llmobs_service.py
@@ -1630,6 +1630,13 @@ def test_submit_evaluation_empty_label_raises_error(llmobs, mock_llmobs_logs):
         )
 
 
+def test_submit_evaluation_label_value_with_a_period_raises_error(llmobs, mock_llmobs_logs):
+    with pytest.raises(ValueError, match="label value must not contain a '.'."):
+        llmobs.submit_evaluation(
+            span={"span_id": "123", "trace_id": "456"}, label="toxicity.0", metric_type="categorical", value="high"
+        )
+
+
 def test_submit_evaluation_incorrect_metric_type_raises_error(llmobs, mock_llmobs_logs):
     with pytest.raises(ValueError, match="metric_type must be one of 'categorical', 'score', or 'boolean'."):
         llmobs.submit_evaluation(