diff --git a/src/documents/tests/test_classifier.py b/src/documents/tests/test_classifier.py
new file mode 100644
index 000000000..1dc859fdb
--- /dev/null
+++ b/src/documents/tests/test_classifier.py
@@ -0,0 +1,87 @@
+import tempfile
+
+from django.test import TestCase, override_settings
+
+from documents.classifier import DocumentClassifier
+from documents.models import Correspondent, Document, Tag, DocumentType
+
+
+class TestClassifier(TestCase):
+
+    def setUp(self):
+
+        self.classifier = DocumentClassifier()
+
+    def generate_test_data(self):
+        self.c1 = Correspondent.objects.create(name="c1", matching_algorithm=Correspondent.MATCH_AUTO)
+        self.c2 = Correspondent.objects.create(name="c2")
+        self.t1 = Tag.objects.create(name="t1", matching_algorithm=Tag.MATCH_AUTO, pk=12)
+        self.t2 = Tag.objects.create(name="t2", matching_algorithm=Tag.MATCH_ANY, pk=34, is_inbox_tag=True)
+        self.t3 = Tag.objects.create(name="t3", matching_algorithm=Tag.MATCH_AUTO, pk=45)
+        self.dt = DocumentType.objects.create(name="dt", matching_algorithm=DocumentType.MATCH_AUTO)
+
+        self.doc1 = Document.objects.create(title="doc1", content="this is a document from c1", correspondent=self.c1, checksum="A", document_type=self.dt)
+        self.doc2 = Document.objects.create(title="doc1", content="this is another document, but from c2", correspondent=self.c2, checksum="B")
+        self.doc_inbox = Document.objects.create(title="doc235", content="aa", checksum="C")
+
+        self.doc1.tags.add(self.t1)
+        self.doc2.tags.add(self.t1)
+        self.doc2.tags.add(self.t3)
+        self.doc_inbox.tags.add(self.t2)
+
+    def testNoTrainingData(self):
+        try:
+            self.classifier.train()
+        except ValueError as e:
+            self.assertEqual(str(e), "No training data available.")
+        else:
+            self.fail("Should raise exception")
+
+    def testEmpty(self):
+        Document.objects.create(title="WOW", checksum="3457", content="ASD")
+        self.classifier.train()
+        self.assertIsNone(self.classifier.document_type_classifier)
+        self.assertIsNone(self.classifier.tags_classifier)
+        self.assertIsNone(self.classifier.correspondent_classifier)
+
+        self.assertListEqual(self.classifier.predict_tags(""), [])
+        self.assertIsNone(self.classifier.predict_document_type(""))
+        self.assertIsNone(self.classifier.predict_correspondent(""))
+
+
+    def testTrain(self):
+        self.generate_test_data()
+        self.classifier.train()
+        self.assertListEqual(list(self.classifier.correspondent_classifier.classes_), [-1, self.c1.pk])
+        self.assertListEqual(list(self.classifier.tags_binarizer.classes_), [self.t1.pk, self.t3.pk])
+
+
+    def testPredict(self):
+        self.generate_test_data()
+        self.classifier.train()
+        self.assertEqual(self.classifier.predict_correspondent(self.doc1.content), self.c1.pk)
+        self.assertEqual(self.classifier.predict_correspondent(self.doc2.content), None)
+        self.assertTupleEqual(self.classifier.predict_tags(self.doc1.content), (self.t1.pk,))
+        self.assertTupleEqual(self.classifier.predict_tags(self.doc2.content), (self.t1.pk,self.t3.pk))
+        self.assertEqual(self.classifier.predict_document_type(self.doc1.content), self.dt.pk)
+        self.assertEqual(self.classifier.predict_document_type(self.doc2.content), None)
+
+    def testDatasetHashing(self):
+
+        self.generate_test_data()
+
+        self.assertTrue(self.classifier.train())
+        self.assertFalse(self.classifier.train())
+
+    @override_settings(DATA_DIR=tempfile.mkdtemp())
+    def testSaveClassifier(self):
+
+        self.generate_test_data()
+
+        self.classifier.train()
+
+        self.classifier.save_classifier()
+
+        newClassifier = DocumentClassifier()
+        newClassifier.reload()
+        self.assertFalse(newClassifier.train())