diff --git a/M/mlpack/build_tarballs.jl b/M/mlpack/build_tarballs.jl
index 65763ce2055..ca9b0276742 100644
--- a/M/mlpack/build_tarballs.jl
+++ b/M/mlpack/build_tarballs.jl
@@ -9,11 +9,11 @@ include(joinpath(YGGDRASIL_DIR, "platforms", "macos_sdks.jl"))
 
 # Set sources and other environment variables.
 name = "mlpack"
-source_version = v"4.7.0"
+source_version = v"4.8.0"
 version = source_version
 sources = [
     ArchiveSource("https://www.mlpack.org/files/mlpack-$(source_version).tar.gz",
-                  "a3f0fb530e51d51f8d7eceb7998b4699906d628000b158ada80541465595324e"),
+                  "0ab06e5c506c7ed5f072faa4c04477c65624e4a1ff62eee8c0d996ef850ec51c"),
 ]
 
 script = raw"""
@@ -115,14 +115,25 @@ products = [
     LibraryProduct("libmlpack_julia_util", :libmlpack_julia_util),
     # Each of these contains a mlpackMain() implementation for the given
     # binding.
-    LibraryProduct("libmlpack_julia_adaboost", :libmlpack_julia_adaboost),
+    LibraryProduct("libmlpack_julia_adaboost_train",
+        :libmlpack_julia_adaboost_train),
+    LibraryProduct("libmlpack_julia_adaboost_classify",
+        :libmlpack_julia_adaboost_classify),
+    LibraryProduct("libmlpack_julia_adaboost_probabilities",
+        :libmlpack_julia_adaboost_probabilities),
     LibraryProduct("libmlpack_julia_approx_kfn", :libmlpack_julia_approx_kfn),
-    LibraryProduct("libmlpack_julia_bayesian_linear_regression",
-        :libmlpack_julia_bayesian_linear_regression),
+    LibraryProduct("libmlpack_julia_bayesian_linear_regression_train",
+        :libmlpack_julia_bayesian_linear_regression_train),
+    LibraryProduct("libmlpack_julia_bayesian_linear_regression_predict",
+        :libmlpack_julia_bayesian_linear_regression_predict),
     LibraryProduct("libmlpack_julia_cf", :libmlpack_julia_cf),
     LibraryProduct("libmlpack_julia_dbscan", :libmlpack_julia_dbscan),
-    LibraryProduct("libmlpack_julia_decision_tree",
-        :libmlpack_julia_decision_tree),
+    LibraryProduct("libmlpack_julia_decision_tree_train",
+        :libmlpack_julia_decision_tree_train),
+    LibraryProduct("libmlpack_julia_decision_tree_classify",
+        :libmlpack_julia_decision_tree_classify),
+    LibraryProduct("libmlpack_julia_decision_tree_probabilities",
+        :libmlpack_julia_decision_tree_probabilities),
     LibraryProduct("libmlpack_julia_det", :libmlpack_julia_det),
     LibraryProduct("libmlpack_julia_emst", :libmlpack_julia_emst),
     LibraryProduct("libmlpack_julia_fastmks", :libmlpack_julia_fastmks),
@@ -146,15 +157,22 @@ products = [
     LibraryProduct("libmlpack_julia_kmeans", :libmlpack_julia_kmeans),
     LibraryProduct("libmlpack_julia_knn", :libmlpack_julia_knn),
     LibraryProduct("libmlpack_julia_krann", :libmlpack_julia_krann),
-    LibraryProduct("libmlpack_julia_lars", :libmlpack_julia_lars),
-    LibraryProduct("libmlpack_julia_linear_regression",
-        :libmlpack_julia_linear_regression),
+    LibraryProduct("libmlpack_julia_lars_train", :libmlpack_julia_lars_train),
+    LibraryProduct("libmlpack_julia_lars_predict", :libmlpack_julia_lars_predict),
+    LibraryProduct("libmlpack_julia_linear_regression_train",
+        :libmlpack_julia_linear_regression_train),
+    LibraryProduct("libmlpack_julia_linear_regression_predict",
+        :libmlpack_julia_linear_regression_predict),
     LibraryProduct("libmlpack_julia_linear_svm", :libmlpack_julia_linear_svm),
     LibraryProduct("libmlpack_julia_lmnn", :libmlpack_julia_lmnn),
     LibraryProduct("libmlpack_julia_local_coordinate_coding",
         :libmlpack_julia_local_coordinate_coding),
-    LibraryProduct("libmlpack_julia_logistic_regression",
-        :libmlpack_julia_logistic_regression),
+    LibraryProduct("libmlpack_julia_logistic_regression_train",
+        :libmlpack_julia_logistic_regression_train),
+    LibraryProduct("libmlpack_julia_logistic_regression_classify",
+        :libmlpack_julia_logistic_regression_classify),
+    LibraryProduct("libmlpack_julia_logistic_regression_probabilities",
+        :libmlpack_julia_logistic_regression_probabilities),
     LibraryProduct("libmlpack_julia_lsh", :libmlpack_julia_lsh),
     LibraryProduct("libmlpack_julia_mean_shift", :libmlpack_julia_mean_shift),
     LibraryProduct("libmlpack_julia_nbc", :libmlpack_julia_nbc),
@@ -173,8 +191,12 @@ products = [
     LibraryProduct("libmlpack_julia_preprocess_split",
         :libmlpack_julia_preprocess_split),
     LibraryProduct("libmlpack_julia_radical", :libmlpack_julia_radical),
-    LibraryProduct("libmlpack_julia_random_forest",
-        :libmlpack_julia_random_forest),
+    LibraryProduct("libmlpack_julia_random_forest_train",
+        :libmlpack_julia_random_forest_train),
+    LibraryProduct("libmlpack_julia_random_forest_classify",
+        :libmlpack_julia_random_forest_classify),
+    LibraryProduct("libmlpack_julia_random_forest_probabilities",
+        :libmlpack_julia_random_forest_probabilities),
     LibraryProduct("libmlpack_julia_softmax_regression",
         :libmlpack_julia_softmax_regression),
     LibraryProduct("libmlpack_julia_sparse_coding",
@@ -196,4 +218,4 @@ dependencies = [
 ]
 
 # Build the tarballs, and possibly a `build.jl` as well.
-build_tarballs(ARGS, name, version, sources, script, platforms, products, dependencies; preferred_gcc_version=v"8", julia_compat="1.7")
+build_tarballs(ARGS, name, version, sources, script, platforms, products, dependencies; preferred_gcc_version=v"9", julia_compat="1.7")