diff --git a/test/nodes/test_ranker.py b/test/nodes/test_ranker.py
index b2b79b4f0..bf1ddcbdd 100644
--- a/test/nodes/test_ranker.py
+++ b/test/nodes/test_ranker.py
@@ -1,5 +1,6 @@
 import pytest
 import math
+from unittest.mock import patch
 
 from haystack.errors import HaystackError
 from haystack.schema import Document
@@ -7,6 +8,63 @@ from haystack.nodes.ranker.base import BaseRanker
 from haystack.nodes.ranker.sentence_transformers import SentenceTransformersRanker
 
 
+@pytest.mark.unit
+def test_ranker_preprocess_batch_queries_and_docs_raises():
+    query_1 = "query 1"
+    query_2 = "query 2"
+    docs = [Document(content="dummy doc 1")]
+    with patch("haystack.nodes.ranker.sentence_transformers.SentenceTransformersRanker.__init__") as mock_ranker_init:
+        mock_ranker_init.return_value = None
+        ranker = SentenceTransformersRanker(model_name_or_path="fake_model")
+    with pytest.raises(HaystackError, match="Number of queries must be 1 if a single list of Documents is provided."):
+        _, _, _, _ = ranker._preprocess_batch_queries_and_docs(queries=[query_1, query_2], documents=docs)
+
+
+@pytest.mark.unit
+def test_ranker_preprocess_batch_queries_and_docs_single_query_single_doc_list():
+    query1 = "query 1"
+    docs1 = [Document(content="dummy doc 1"), Document(content="dummy doc 2")]
+    with patch("haystack.nodes.ranker.sentence_transformers.SentenceTransformersRanker.__init__") as mock_ranker_init:
+        mock_ranker_init.return_value = None
+        ranker = SentenceTransformersRanker(model_name_or_path="fake_model")
+    num_of_docs, all_queries, all_docs, single_list_of_docs = ranker._preprocess_batch_queries_and_docs(
+        queries=[query1], documents=docs1
+    )
+    assert single_list_of_docs is True
+    assert num_of_docs == [2]
+    assert len(all_queries) == 2
+    assert len(all_docs) == 2
+
+
+@pytest.mark.unit
+def test_ranker_preprocess_batch_queries_and_docs_multiple_queries_multiple_doc_lists():
+    query_1 = "query 1"
+    query_2 = "query 2"
+    docs1 = [Document(content="dummy doc 1"), Document(content="dummy doc 2")]
+    docs2 = [Document(content="dummy doc 3")]
+    with patch("haystack.nodes.ranker.sentence_transformers.SentenceTransformersRanker.__init__") as mock_ranker_init:
+        mock_ranker_init.return_value = None
+        ranker = SentenceTransformersRanker(model_name_or_path="fake_model")
+    num_of_docs, all_queries, all_docs, single_list_of_docs = ranker._preprocess_batch_queries_and_docs(
+        queries=[query_1, query_2], documents=[docs1, docs2]
+    )
+    assert single_list_of_docs is False
+    assert num_of_docs == [2, 1]
+    assert len(all_queries) == 3
+    assert len(all_docs) == 3
+
+
+@pytest.mark.unit
+def test_ranker_get_batches():
+    all_queries = ["query 1", "query 1"]
+    all_docs = [Document(content="dummy doc 1"), Document(content="dummy doc 2")]
+    batches = SentenceTransformersRanker._get_batches(all_queries=all_queries, all_docs=all_docs, batch_size=None)
+    assert next(batches) == (all_queries, all_docs)
+
+    batches = SentenceTransformersRanker._get_batches(all_queries=all_queries, all_docs=all_docs, batch_size=1)
+    assert next(batches) == (all_queries[0:1], all_docs[0:1])
+
+
 def test_ranker(ranker):
     query = "What is the most important building in King's Landing that has a religious background?"
     docs = [