diff --git a/neuralNetworkTests.c b/neuralNetworkTests.c
index 21ab370..9be45e2 100644
--- a/neuralNetworkTests.c
+++ b/neuralNetworkTests.c
@@ -4,13 +4,47 @@
 #include <math.h>
 #include "unity.h"
 #include "neuralNetwork.h"
-
+//Dateischichten sind in neuralNetwork.h definiert
+// Dateiname: __info2_neural_network_file_format__
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // TODO
+    FILE *file = fopen(path, "wb");
+    if (!file) return;
+
+    // Header schreiben
+    fwrite(FILE_HEADER_STRING, 1, strlen(FILE_HEADER_STRING), file);
+
+    // Anzahl Layer schreiben
+    uint32_t nLayers = nn.numberOfLayers;
+    fwrite(&nLayers, sizeof(uint32_t), 1, file);
+
+    for (uint32_t i = 0; i < nLayers; i++) {
+        Layer layer = nn.layers[i];
+
+        // Weights-Dimensionen
+        uint32_t rW = layer.weights.rows;
+        uint32_t cW = layer.weights.cols;
+        fwrite(&rW, sizeof(uint32_t), 1, file);
+        fwrite(&cW, sizeof(uint32_t), 1, file);
+
+        // Weights-Werte
+        fwrite(layer.weights.buffer, sizeof(MatrixType), rW * cW, file);
+
+        // Bias-Dimensionen
+        uint32_t rB = layer.biases.rows;
+        uint32_t cB = layer.biases.cols;
+        fwrite(&rB, sizeof(uint32_t), 1, file);
+        fwrite(&cB, sizeof(uint32_t), 1, file);
+
+        // Bias-Werte
+        fwrite(layer.biases.buffer, sizeof(MatrixType), rB * cB, file);
+    }
+
+    fclose(file);
 }
 
+
 void test_loadModelReturnsCorrectNumberOfLayers(void)
 {
     const char *path = "some__nn_test_file.info2";