diff --git a/tests/fixtures/monthly_subquota_limit_classifier.csv b/tests/fixtures/monthly_subquota_limit_classifier.csv
new file mode 100644
index 0000000..4d4b917
--- /dev/null
+++ b/tests/fixtures/monthly_subquota_limit_classifier.csv
@@ -0,0 +1,10 @@
+applicant_id,document_id,issue_date,year,month,subquota_number,total_net_value
+1,100,2015-03-01,2015,3,120,10500
+1,100,2015-03-01,2015,3,120,401
+2,100,2015-04-01,2015,4,120,10500
+2,100,2015-04-01,2015,4,120,399
+3,100,2015-05-01,2015,5,120,10500
+3,100,2015-05-01,2015,5,120,400
+4,100,2015-06-01,2015,6,120,10500
+4,100,2015-06-01,2015,6,120,401
+5,100,2015-06-01,2015,6,120,10500
diff --git a/tests/test_monthly_subquota_limit_classifier.py b/tests/test_monthly_subquota_limit_classifier.py
new file mode 100644
index 0000000..124281d
--- /dev/null
+++ b/tests/test_monthly_subquota_limit_classifier.py
@@ -0,0 +1,19 @@
+from unittest import TestCase
+
+import numpy as np
+import pandas as pd
+from rosie.monthly_subquota_limit_classifier import MonthlySubquotaLimitClassifier
+
+
+class TestMonthlySubquotaLimitClassifier(TestCase):
+
+    def setUp(self):
+        self.dataset = pd.read_csv('tests/fixtures/monthly_subquota_limit_classifier.csv',
+                                   dtype={'subquota_number': np.str})
+        self.subject = MonthlySubquotaLimitClassifier()
+        self.subject.fit_transform(self.dataset)
+        self.prediction = self.subject.predict(self.dataset)
+
+    def test_predict_false_when_not_in_date_range(self):
+        self.assertEqual(False, self.prediction[0])
+        self.assertEqual(False, self.prediction[1])