diff --git a/onnxruntime/core/providers/webnn/builders/model_builder.cc b/onnxruntime/core/providers/webnn/builders/model_builder.cc
index e8f116d390..097dd16307 100644
--- a/onnxruntime/core/providers/webnn/builders/model_builder.cc
+++ b/onnxruntime/core/providers/webnn/builders/model_builder.cc
@@ -75,9 +75,18 @@ InitializedTensorSet ModelBuilder::GetInitializerTensors() {
 }
 
 void ModelBuilder::PreprocessInitializers() {
+  const auto& initializers = graph_viewer_.GetAllInitializedTensors();
   const auto& node_indices = graph_viewer_.GetNodesInTopologicalOrder();
   for (size_t i = 0; i < node_indices.size(); i++) {
     const auto* node(graph_viewer_.GetNode(node_indices[i]));
+
+    // find all initializers consumed. AddInitializersToSkip will potentially decrement the usage count.
+    for (const auto* input : node->InputDefs()) {
+      if (input->Exists() && Contains(initializers, input->Name())) {
+        initializer_usage_[input->Name()]++;
+      }
+    }
+
     if (const auto* op_builder = GetOpBuilder(*node)) {
       op_builder->AddInitializersToSkip(*this, *node);
     }
@@ -90,12 +99,11 @@ Status ModelBuilder::RegisterInitializers() {
     const auto& name = tensor.name();
     const auto& shape = tensor.dims();
 
-    // Ignore the following tensors:
-    // 1. Empty tensors: optional tensors can be indicated by an empty name.
-    // 2. Tensors in skipped_initializers_: These are tensors that are not used as WebNN Constants.
-    //    Note: Scalar tensors are excluded because ONNX Runtime will optimize same scalar initializers into one.
-    if (name.empty() || (Contains(skipped_initializers_, name) && !shape.empty()))
+    // skip initializer if there is no remaining usage
+    auto usage_count = initializer_usage_[name];
+    if (usage_count == 0) {
       continue;
+    }
 
     std::vector<int32_t> dims;
     // When the shape is empty, it is scalar initializer that dims = {};
@@ -385,7 +393,13 @@ void ModelBuilder::AddOperand(const std::string& name, const emscripten::val& op
 }
 
 void ModelBuilder::AddInitializerToSkip(const std::string& tensor_name) {
-  skipped_initializers_.insert(tensor_name);
+  // Decrement usage count if this is a known initializer.
+  // For simplicity the OpBuilder::AddInitializersToSkip implementations may call this for arbitrary input names
+  // without first checking if the value is an initializer.
+  auto entry = initializer_usage_.find(tensor_name);
+  if (entry != initializer_usage_.end()) {
+    --entry->second;
+  }
 }
 
 void ModelBuilder::AddInputToSkip(const std::string& input_name) {
diff --git a/onnxruntime/core/providers/webnn/builders/model_builder.h b/onnxruntime/core/providers/webnn/builders/model_builder.h
index 0fc2fa2067..4e2d84f481 100644
--- a/onnxruntime/core/providers/webnn/builders/model_builder.h
+++ b/onnxruntime/core/providers/webnn/builders/model_builder.h
@@ -81,7 +81,7 @@ class ModelBuilder {
 
   InlinedHashMap<std::string, OnnxTensorInfo> input_output_info_;
 
-  InlinedHashSet<std::string> skipped_initializers_;
+  std::unordered_map<std::string, int> initializer_usage_;
   InlinedHashSet<std::string> skipped_inputs_;
 
   uint32_t name_token_{0};