diff --git a/matrix.c b/matrix.c
index 4474836..253d848 100644
--- a/matrix.c
+++ b/matrix.c
@@ -8,9 +8,10 @@
 Matrix createMatrix(unsigned int rows, unsigned int cols)
 {
     Matrix matrix;
+    matrix.buffer = NULL;
     matrix.rows = 0;
     matrix.cols = 0;
-    matrix.buffer = NULL;
+    
 
     // Wenn die Dimensionen gültig sind, Speicher reservieren
     if (rows > 0 && cols > 0) 
diff --git a/matrix.h b/matrix.h
index c85e38c..02202c5 100644
--- a/matrix.h
+++ b/matrix.h
@@ -8,9 +8,10 @@ typedef float MatrixType;
 // TODO Matrixtyp definieren
 typedef struct 
 {
+    MatrixType *buffer;
     unsigned int rows;
     unsigned int cols;
-    MatrixType *buffer;
+    
 } Matrix; 
 
 
diff --git a/neuralNetworkTests.c b/neuralNetworkTests.c
index 21ab370..8335c87 100644
--- a/neuralNetworkTests.c
+++ b/neuralNetworkTests.c
@@ -8,7 +8,47 @@
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-    // TODO
+    // TODO : Fehlerbehandlung
+  FILE *file = fopen(path, "wb");
+    if (!file) {
+        perror("Fehler beim Öffnen der Datei");
+        return;
+    }
+
+    const char *header = "__info2_neural_network_file_format__";
+    fwrite(header, sizeof(char), strlen(header), file);
+
+    for (unsigned int i = 0; i < nn.numberOfLayers; i++) {
+        Layer layer = nn.layers[i];
+
+        unsigned int inputDim = (i == 0) ? layer.weights.cols : 0; // nur beim ersten Layer
+        unsigned int outputDim = layer.weights.rows;
+
+        if (i == 0) {
+            // erstes Layer: inputDim und outputDim schreiben
+            fwrite(&inputDim, sizeof(unsigned int), 1, file);
+            fwrite(&outputDim, sizeof(unsigned int), 1, file);
+        } else {
+            // nur outputDim für weitere Layer
+            fwrite(&outputDim, sizeof(unsigned int), 1, file);
+        }
+
+        fwrite(layer.weights.buffer, sizeof(MatrixType), layer.weights.rows * layer.weights.cols, file);
+        fwrite(layer.biases.buffer, sizeof(MatrixType), layer.biases.rows * layer.biases.cols, file);
+    }
+
+    unsigned int zero = 0;
+    fwrite(&zero, sizeof(unsigned int), 1, file);
+    fclose(file);
+
+    // Debug
+    printf("prepareNeuralNetworkFile: Datei '%s' erstellt mit %u Layer(n)\n", path, nn.numberOfLayers);
+    for (unsigned int i = 0; i < nn.numberOfLayers; i++) {
+        Layer layer = nn.layers[i];
+        printf("Layer %u: weights (%u x %u), biases (%u x %u)\n", 
+               i, layer.weights.rows, layer.weights.cols, layer.biases.rows, layer.biases.cols);
+    }
+
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)