diff --git a/src/main/java/net/echo/brain4j/model/impl/FeedForwardModel.java b/src/main/java/net/echo/brain4j/model/impl/FeedForwardModel.java
index a6b5c34..fee9824 100644
--- a/src/main/java/net/echo/brain4j/model/impl/FeedForwardModel.java
+++ b/src/main/java/net/echo/brain4j/model/impl/FeedForwardModel.java
@@ -90,7 +90,7 @@ public double fit(DataSet set) {
 
     @Override
     public double[] predict(double ... input) {
-        Layer inputLayer = layers.getFirst();
+        Layer inputLayer = layers.get(0);
 
         if (input.length != inputLayer.getNeurons().size()) {
             throw new IllegalArgumentException("Input size does not match model's input dimension!");
@@ -129,7 +129,7 @@ public double[] predict(double ... input) {
             nextLayer.applyFunction();
         }
 
-        Layer outputLayer = layers.getLast();
+        Layer outputLayer = layers.get(layers.size() - 1);
         double[] output = new double[outputLayer.getNeurons().size()];
 
         for (int i = 0; i < output.length; i++) {
diff --git a/src/main/java/net/echo/brain4j/training/BackPropagation.java b/src/main/java/net/echo/brain4j/training/BackPropagation.java
index b403c8b..3e80294 100644
--- a/src/main/java/net/echo/brain4j/training/BackPropagation.java
+++ b/src/main/java/net/echo/brain4j/training/BackPropagation.java
@@ -73,7 +73,7 @@ private void backpropagate(double[] targets, double[] outputs, double learningRa
     }
 
     private void initialDelta(List<Layer> layers, double[] targets, double[] outputs) {
-        Layer outputLayer = layers.getLast();
+        Layer outputLayer = layers.get(layers.size() - 1);
 
         for (int i = 0; i < outputLayer.getNeurons().size(); i++) {
             Neuron neuron = outputLayer.getNeuronAt(i);