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diff --git a/src/main/java/org/apache/commons/math3/distribution/MixtureMultivariateNormalDistribution.java b/src/main/java/org/apache/commons/math3/distribution/MixtureMultivariateNormalDistribution.java
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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.commons.math3.distribution;
+
+import org.apache.commons.math3.exception.DimensionMismatchException;
+import org.apache.commons.math3.exception.NotPositiveException;
+import org.apache.commons.math3.random.RandomGenerator;
+import org.apache.commons.math3.util.Pair;
+
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * Multivariate normal mixture distribution. This class is mainly syntactic sugar.
+ *
+ * @see MixtureMultivariateRealDistribution
+ * @since 3.2
+ */
+public class MixtureMultivariateNormalDistribution
+        extends MixtureMultivariateRealDistribution<MultivariateNormalDistribution> {
+
+    /**
+     * Creates a multivariate normal mixture distribution.
+     *
+     * <p><b>Note:</b> this constructor will implicitly create an instance of {@link
+     * org.apache.commons.math3.random.Well19937c Well19937c} as random generator to be used for
+     * sampling only (see {@link #sample()} and {@link #sample(int)}). In case no sampling is needed
+     * for the created distribution, it is advised to pass {@code null} as random generator via the
+     * appropriate constructors to avoid the additional initialisation overhead.
+     *
+     * @param weights Weights of each component.
+     * @param means Mean vector for each component.
+     * @param covariances Covariance matrix for each component.
+     */
+    public MixtureMultivariateNormalDistribution(
+            double[] weights, double[][] means, double[][][] covariances) {
+        super(createComponents(weights, means, covariances));
+    }
+
+    /**
+     * Creates a mixture model from a list of distributions and their associated weights.
+     *
+     * <p><b>Note:</b> this constructor will implicitly create an instance of {@link
+     * org.apache.commons.math3.random.Well19937c Well19937c} as random generator to be used for
+     * sampling only (see {@link #sample()} and {@link #sample(int)}). In case no sampling is needed
+     * for the created distribution, it is advised to pass {@code null} as random generator via the
+     * appropriate constructors to avoid the additional initialisation overhead.
+     *
+     * @param components List of (weight, distribution) pairs from which to sample.
+     */
+    public MixtureMultivariateNormalDistribution(
+            List<Pair<Double, MultivariateNormalDistribution>> components) {
+        super(components);
+    }
+
+    /**
+     * Creates a mixture model from a list of distributions and their associated weights.
+     *
+     * @param rng Random number generator.
+     * @param components Distributions from which to sample.
+     * @throws NotPositiveException if any of the weights is negative.
+     * @throws DimensionMismatchException if not all components have the same number of variables.
+     */
+    public MixtureMultivariateNormalDistribution(
+            RandomGenerator rng, List<Pair<Double, MultivariateNormalDistribution>> components)
+            throws NotPositiveException, DimensionMismatchException {
+        super(rng, components);
+    }
+
+    /**
+     * @param weights Weights of each component.
+     * @param means Mean vector for each component.
+     * @param covariances Covariance matrix for each component.
+     * @return the list of components.
+     */
+    private static List<Pair<Double, MultivariateNormalDistribution>> createComponents(
+            double[] weights, double[][] means, double[][][] covariances) {
+        final List<Pair<Double, MultivariateNormalDistribution>> mvns =
+                new ArrayList<Pair<Double, MultivariateNormalDistribution>>(weights.length);
+
+        for (int i = 0; i < weights.length; i++) {
+            final MultivariateNormalDistribution dist =
+                    new MultivariateNormalDistribution(means[i], covariances[i]);
+
+            mvns.add(new Pair<Double, MultivariateNormalDistribution>(weights[i], dist));
+        }
+
+        return mvns;
+    }
+}