diff --git a/src/main/java/ExampleXORBlankLayers.java b/src/main/java/ExampleXORBlankLayers.java
new file mode 100644
index 0000000..2dca672
--- /dev/null
+++ b/src/main/java/ExampleXORBlankLayers.java
@@ -0,0 +1,32 @@
+import org.ejml.simple.SimpleMatrix;
+
+public class ExampleXORBlankLayers {
+    public static void main(String[] args) {
+        SimpleMatrix[] X_train = {new SimpleMatrix(new double[][]{{0, 0}}),
+                new SimpleMatrix(new double[][]{{0, 1}}),
+                new SimpleMatrix(new double[][]{{1, 0}}),
+                new SimpleMatrix(new double[][]{{1, 1}})};
+        SimpleMatrix[] y_train = {new SimpleMatrix(new double[][]{{0}}),
+                new SimpleMatrix(new double[][]{{1}}),
+                new SimpleMatrix(new double[][]{{1}}),
+                new SimpleMatrix(new double[][]{{0}})};
+
+        Network network = new Network();
+        network.addLayer(new BlankLayer(2));
+        network.addLayer(new ActivationLayer(ActivationFunctions::tanh, ActivationFunctions::tanhPrime));
+        network.addLayer(new BlankLayer(1));
+        network.addLayer(new ActivationLayer(ActivationFunctions::tanh, ActivationFunctions::tanhPrime));
+        network.addNeuron(0, 2);
+
+        network.use(LossFunctions::MSE, LossFunctions::MSEPrime);
+        network.fit(X_train, y_train, 1000, 0.1d);
+
+        SimpleMatrix[] output = network.predict(X_train);
+        for (SimpleMatrix entry : output) {
+            System.out.println("Prediction:");
+            for (int i = 0; i < entry.getNumElements(); i++) {
+                System.out.println(Math.round(entry.get(i)));
+            }
+        }
+    }
+}