diff --git a/test/TritonIntelGPU/match-target-size.mlir b/test/TritonIntelGPU/match-target-size.mlir
index f5452d4a5e..2c26411a07 100644
--- a/test/TritonIntelGPU/match-target-size.mlir
+++ b/test/TritonIntelGPU/match-target-size.mlir
@@ -142,6 +142,51 @@ tt.func public @simplify_scf_for(%arg0: tensor<16x8xf16>, %arg1: tensor<16x8xf16
 
 // -----
 
+// COM: Test SCF canonicalization: ensure loop canonicalization can be applied to dependendent loops
+tt.func public @simplify_scf_for(%arg0: tensor<16x8xf16>, %arg1: tensor<16x8xf16>, %arg2: !tt.ptr<f16, 1>,
+                                 %arg3: i64, %arg4: i64, %arg5: i64, %arg6: i32, %arg7: i32) {
+  // CHECK-LABEL: @simplify_scf_for
+  // CHECK-NOT: triton_intel_gpu.glue
+  // CHECK:      [[RES:%.*]]:2 = scf.for {{.*}} iter_args([[INIT1:%.*]] = %arg0, [[INIT2:%.*]] = %arg1)
+  // CHECK-SAME:               -> (tensor<16x8xf16>, tensor<16x8xf16>) : i32 {
+  // CHECK-NEXT:   scf.yield [[INIT2]], [[INIT1]] : tensor<16x8xf16>, tensor<16x8xf16>
+  // CHECK-NEXT: }
+  // CHECK:      [[RES2:%.*]]:2 = scf.for {{.*}} iter_args([[INIT3:%.*]] = [[RES]]#0, [[INIT4:%.*]] = [[RES]]#1)
+  // CHECK-SAME:               -> (tensor<16x8xf16>, tensor<16x8xf16>) : i32 {
+  // CHECK-NEXT:   scf.yield [[INIT3]], [[INIT4]] : tensor<16x8xf16>, tensor<16x8xf16>
+  // CHECK-NEXT: }
+  // CHECK-NEXT: [[GLUE:%.*]] = triton_intel_gpu.glue [[RES2]]#1, [[RES2]]#0
+  // CHECK-SAME:              : (tensor<16x8xf16>, tensor<16x8xf16>) -> tensor<16x16xf16>
+  // CHECK-NEXT: [[PTR:%.*]] = tt.make_tensor_ptr %arg2
+  // CHECK-NEXT: tt.store [[PTR]], [[GLUE]]
+  %lb = arith.constant 0 : i32
+  %ub = arith.constant 32 : i32
+  %st = arith.constant 1 : i32
+  %c1_i64 = arith.constant 1 : i64
+  %cst = arith.constant dense<42.0> : tensor<16x16xf16>
+  %glue = triton_intel_gpu.glue %arg0, %arg1 : (tensor<16x8xf16>, tensor<16x8xf16>) -> tensor<16x16xf16>
+  %res = scf.for %iv = %lb to %ub step %st iter_args(%arg = %glue) -> (tensor<16x16xf16>) : i32 {
+    %e1 = triton_intel_gpu.extract %arg[1] : tensor<16x16xf16> -> tensor<16x8xf16>
+    %e2 = triton_intel_gpu.extract %arg[0] : tensor<16x16xf16> -> tensor<16x8xf16>
+    %g1 = triton_intel_gpu.glue %e1, %e2 : (tensor<16x8xf16>, tensor<16x8xf16>) -> tensor<16x16xf16>
+    scf.yield %g1 : tensor<16x16xf16>
+  }
+  %res2 = scf.for %iv = %lb to %ub step %st iter_args(%arg = %res) -> (tensor<16x16xf16>) : i32 {
+    %e1 = triton_intel_gpu.extract %arg[0] : tensor<16x16xf16> -> tensor<16x8xf16>
+    %e2 = triton_intel_gpu.extract %arg[1] : tensor<16x16xf16> -> tensor<16x8xf16>
+    %g1 = triton_intel_gpu.glue %e1, %e2 : (tensor<16x8xf16>, tensor<16x8xf16>) -> tensor<16x16xf16>
+    scf.yield %g1 : tensor<16x16xf16>
+  }
+  %e3 = triton_intel_gpu.extract %res2[0] : tensor<16x16xf16> -> tensor<16x8xf16>
+  %e4 = triton_intel_gpu.extract %res2[1] : tensor<16x16xf16> -> tensor<16x8xf16>
+  %g2 = triton_intel_gpu.glue %e4, %e3 : (tensor<16x8xf16>, tensor<16x8xf16>) -> tensor<16x16xf16>
+  %ptr = tt.make_tensor_ptr %arg2, [%arg3, %arg4], [%arg5, %c1_i64], [%arg6, %arg7] {order = array<i32: 1, 0>} : <tensor<16x16xf16>>
+  tt.store %ptr, %g2 {boundaryCheck = array<i32: 0, 1>, cache = 1 : i32, evict = 1 : i32} : !tt.ptr<tensor<16x16xf16>>
+  tt.return
+}
+
+// -----
+
 // COM: Test transformation for int8 datatype
 
 // CHECK-LABEL: @matmul_kernel_with_block_pointers_int8
diff --git a/third_party/intel/lib/TritonIntelGPUTransforms/MatchTargetSize.cpp b/third_party/intel/lib/TritonIntelGPUTransforms/MatchTargetSize.cpp
index 089a498c37..bc411670d2 100644
--- a/third_party/intel/lib/TritonIntelGPUTransforms/MatchTargetSize.cpp
+++ b/third_party/intel/lib/TritonIntelGPUTransforms/MatchTargetSize.cpp
@@ -512,31 +512,31 @@ class ScfPattern : public OpRewritePattern<scf::ForOp> {
     rewriter.create<scf::YieldOp>(yield.getLoc(), newValues);
     rewriter.eraseOp(yield);
 
-    // Replace uses of the original loop results with the new loop results.
-    userIndexMap.clear();
+    rewriter.setInsertionPointAfter(newForOp);
+
     idx = 0;
     for (auto [result, init] :
          llvm::zip(forOp.getResults(), forOp.getInits())) {
       Operation *definingOp = init.getDefiningOp();
+
+      // Loop-carried value was not split by this pattern, just rewire all users
+      // to the new scf.for operation.
       if (!isa_and_nonnull<ttgi::GlueOp>(definingOp)) {
-        userIndexMap[result] = idx++;
+        result.replaceAllUsesWith(newForOp.getResults()[idx]);
+        ++idx;
         continue;
       }
 
+      // Re-glue individual results together _after_ the loop. This enables
+      // canonicalization of extract ops and dependent loops.
       auto glue = cast<ttgi::GlueOp>(definingOp);
-      for (Operation *user : result.getUsers()) {
-        if (auto extract = dyn_cast<ttgi::ExtractOp>(user)) {
-          userIndexMap[extract] = idx + extract.getIndex();
-          deleteList.push_back(extract.getOperation());
-        }
-      }
-
+      auto reglue = rewriter.create<ttgi::GlueOp>(
+          forOp->getLoc(), result.getType(),
+          newForOp->getResults().slice(idx, glue.getOperands().size()));
+      result.replaceAllUsesWith(reglue);
       idx += glue->getOperands().size();
     }
 
-    for (auto [user, idx] : userIndexMap)
-      user.replaceAllUsesWith(newForOp.getResults()[idx]);
-
     for (Operation *deleteOp : deleteList)
       rewriter.eraseOp(deleteOp);
 
@@ -567,10 +567,11 @@ class ScfPattern : public OpRewritePattern<scf::ForOp> {
         return false;
     }
 
-    // Bail out if the loop result is not used by an 'extract' operation.
+    // Bail out if the loop result is not used by an 'extract' operation, or
+    // another loop.
     if (forOp->getNumResults() == 1 &&
         llvm::any_of(forOp.getResult(0).getUsers(), [](Operation *user) {
-          return !isa<ttgi::ExtractOp>(user);
+          return !isa<ttgi::ExtractOp, scf::ForOp>(user);
         }))
       return false;