diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index 972ddd9b3..a4c957d3a 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -35,6 +35,7 @@ set(XCSF_TESTS
     neural_layer_lstm_test.cpp
     neural_layer_maxpool_test.cpp
     neural_layer_recurrent_test.cpp
+    neural_layer_softmax_test.cpp
     neural_test.cpp
     pa_test.cpp
     pred_nlms_test.cpp
diff --git a/test/neural_layer_softmax_test.cpp b/test/neural_layer_softmax_test.cpp
new file mode 100644
index 000000000..fa9b5d0be
--- /dev/null
+++ b/test/neural_layer_softmax_test.cpp
@@ -0,0 +1,123 @@
+/*
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+
+/**
+ * @file neural_layer_softmax_test.cpp
+ * @author Richard Preen <rpreen@gmail.com>
+ * @copyright The Authors.
+ * @date 2023.
+ * @brief Softmax neural network layer tests.
+ */
+
+#include "../lib/doctest/doctest/doctest.h"
+#include <iostream>
+#include <sstream>
+
+extern "C" {
+#include "../xcsf/cl.h"
+#include "../xcsf/neural.h"
+#include "../xcsf/neural_activations.h"
+#include "../xcsf/neural_layer.h"
+#include "../xcsf/neural_layer_softmax.h"
+#include "../xcsf/param.h"
+#include "../xcsf/prediction.h"
+#include "../xcsf/utils.h"
+#include "../xcsf/xcsf.h"
+#include <math.h>
+#include <stdbool.h>
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+}
+
+TEST_CASE("NEURAL_LAYER_SOFTMAX")
+{
+    /* Test initialisation */
+    struct XCSF xcsf;
+    struct Net net;
+    struct Layer *l;
+    rand_init();
+    param_init(&xcsf, 10, 2, 1);
+    pred_param_set_type(&xcsf, PRED_TYPE_NEURAL);
+    neural_init(&net);
+    struct ArgsLayer args;
+    layer_args_init(&args);
+    args.type = SOFTMAX;
+    args.n_inputs = 3;
+    args.scale = 1;
+    layer_args_validate(&args);
+    l = layer_init(&args);
+    neural_push(&net, l);
+    CHECK_EQ(l->n_inputs, 3);
+    CHECK_EQ(l->scale, 1);
+
+    /* Test one forward pass of input */
+    const double x[3] = { 0.2, 0.5, 0.3 };
+    const double output[3] = { 0.289433, 0.390694, 0.319873 };
+    neural_layer_softmax_forward(l, &net, x);
+    double *out = neural_layer_softmax_output(l);
+    double sum = 0;
+    for (int i = 0; i < l->n_outputs; ++i) {
+        CHECK_EQ(doctest::Approx(out[i]), output[i]);
+        sum += l->output[i];
+    }
+    CHECK_EQ(doctest::Approx(sum), 1);
+
+    /* Test one backward pass of input */
+    double delta[3] = { 0.2, 0.3, 0.4 };
+    memcpy(l->delta, delta, sizeof(double) * 3);
+    neural_layer_softmax_backward(l, &net, x, delta);
+    for (int i = 0; i < 3; ++i) {
+        CHECK_EQ(doctest::Approx(l->delta[i] * 2), delta[i]);
+    }
+
+    /* Test update */
+    neural_layer_softmax_update(l);
+
+    /* Test copy */
+    struct Layer *l2 = neural_layer_softmax_copy(l);
+    CHECK_EQ(l->type, l2->type);
+    CHECK_EQ(l->options, l2->options);
+    CHECK_EQ(l->out_w, l2->out_w);
+    CHECK_EQ(l->out_h, l2->out_h);
+    CHECK_EQ(l->out_c, l2->out_c);
+    CHECK_EQ(l->max_outputs, l2->max_outputs);
+    CHECK_EQ(l->n_inputs, l2->n_inputs);
+    CHECK_EQ(l->n_outputs, l2->n_outputs);
+    CHECK_EQ(l->scale, l2->scale);
+
+    /* Test mutate */
+    CHECK_EQ(neural_layer_softmax_mutate(l), false);
+
+    /* Test randomisation */
+    neural_layer_softmax_rand(l);
+
+    /* Smoke test export */
+    char *json_str = neural_layer_softmax_json_export(l, true);
+    CHECK(json_str != NULL);
+
+    /* Test serialization */
+    FILE *fp = fopen("temp.bin", "wb");
+    size_t w = neural_layer_softmax_save(l, fp);
+    fclose(fp);
+    fp = fopen("temp.bin", "rb");
+    size_t r = neural_layer_softmax_load(l, fp);
+    CHECK_EQ(w, r);
+    fclose(fp);
+
+    /* Test clean */
+    neural_free(&net);
+    param_free(&xcsf);
+}