diff --git a/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp b/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp
--- a/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp
+++ b/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp
@@ -233,6 +233,54 @@
     return success();
   }
 };
+
+template <>
+struct ConvertTosaOp<tosa::SelectOp> : public OpRewritePattern<tosa::SelectOp> {
+  using OpRewritePattern<tosa::SelectOp>::OpRewritePattern;
+
+  LogicalResult matchAndRewrite(tosa::SelectOp tosaOp,
+                                PatternRewriter &rewriter) const override {
+
+    Value input1 = tosaOp.getOnTrue();
+    Value input2 = tosaOp.getOnFalse();
+    Value pred = tosaOp.getPred();
+    Value output = tosaOp.getResult();
+
+    auto outputType = output.getType().dyn_cast<RankedTensorType>();
+    if (!outputType)
+      return failure();
+
+    Value newInput1, newInput2, newPred1, newPred2;
+    bool reshaped1 = reshapeLowerToHigher(rewriter, tosaOp.getLoc(), outputType,
+                                          pred, input1, newPred1, newInput1)
+                         .succeeded();
+
+    bool reshaped2 = reshapeLowerToHigher(rewriter, tosaOp.getLoc(), outputType,
+                                          pred, input2, newPred2, newInput2)
+                         .succeeded();
+
+    // Both operands are fail to reshape, no need to perform broadcast.
+    if (!reshaped1 && !reshaped2)
+      return failure();
+
+    // Verify the rank of operands agrees with each other.
+    if (reshaped1 && reshaped2) {
+      if (newPred1.getType().dyn_cast<RankedTensorType>().getRank() !=
+          newPred2.getType().dyn_cast<RankedTensorType>().getRank()) {
+        return failure();
+      }
+    }
+
+    Value outInput1 = reshaped1 ? newInput1 : input1;
+    Value outInput2 = reshaped2 ? newInput2 : input2;
+    Value outPred = reshaped1 ? newPred1 : (reshaped2 ? newPred2 : pred);
+
+    rewriter.replaceOpWithNewOp<tosa::SelectOp>(tosaOp, outputType, outPred,
+                                                outInput1, outInput2);
+
+    return success();
+  }
+};
 } // namespace
 
 namespace {
@@ -265,6 +313,7 @@
     patterns.add<ConvertTosaOp<tosa::LogicalOrOp>>(ctx);
     patterns.add<ConvertTosaOp<tosa::LogicalXorOp>>(ctx);
     patterns.add<ConvertTosaOp<tosa::PowOp>>(ctx);
+    patterns.add<ConvertTosaOp<tosa::SelectOp>>(ctx);
     (void)applyPatternsAndFoldGreedily(func, std::move(patterns));
   }
 };
diff --git a/mlir/test/Dialect/Tosa/broadcast.mlir b/mlir/test/Dialect/Tosa/broadcast.mlir
--- a/mlir/test/Dialect/Tosa/broadcast.mlir
+++ b/mlir/test/Dialect/Tosa/broadcast.mlir
@@ -195,3 +195,32 @@
   %0 = "tosa.add"(%arg0, %arg1) : (tensor<i32>, tensor<17x16x15x14xi32>) -> tensor<17x16x15x14xi32>
   return %0 : tensor<17x16x15x14xi32>
 }
+
+// -----
+// CHECK-LABEL: broadcast_select1
+func.func @test_broadcast_select1(%arg0: tensor<1x16x16xi1>, %arg1: tensor<f32>, %arg2: tensor<f32>) -> tensor<1x16x16xf32> {
+  // CHECK-DAG: %[[VAL_0:.*]] = "tosa.reshape"(%arg1) {new_shape = [1, 1, 1]}
+  // CHECK-DAG: %[[VAL_1:.*]] = "tosa.reshape"(%arg2) {new_shape = [1, 1, 1]}
+  // CHECK: %[[VAL_2:.*]] = "tosa.select"(%arg0, %[[VAL_0]], %[[VAL_1]])
+  %0 = "tosa.select"(%arg0, %arg1, %arg2) : (tensor<1x16x16xi1>, tensor<f32>, tensor<f32>) -> tensor<1x16x16xf32>
+  return %0 : tensor<1x16x16xf32>
+}
+
+// -----
+// CHECK-LABEL: broadcast_select2
+func.func @test_broadcast_select2(%arg0: tensor<17x16x15x14xi1>, %arg1: tensor<17x16x15x14xf32>, %arg2: tensor<f32>) -> tensor<17x16x15x14xf32> {
+  // CHECK-DAG: %[[VAL_0:.*]] = "tosa.reshape"(%arg2) {new_shape = [1, 1, 1, 1]}
+  // CHECK: %[[VAL_1:.*]] = "tosa.select"(%arg0, %arg1, %[[VAL_0]])
+  %0 = "tosa.select"(%arg0, %arg1, %arg2) : (tensor<17x16x15x14xi1>, tensor<17x16x15x14xf32>, tensor<f32>) -> tensor<17x16x15x14xf32>
+  return %0 : tensor<17x16x15x14xf32>
+}
+
+// -----
+// CHECK-LABEL: broadcast_select3
+func.func @test_broadcast_select3(%arg0: tensor<i1>, %arg1: tensor<32x8xf32>, %arg2: tensor<1x32x32x8xf32>) -> tensor<1x32x32x8xf32> {
+  // CHECK-DAG: %[[VAL_0:.*]] = "tosa.reshape"(%arg0) {new_shape = [1, 1, 1, 1]}
+  // CHECK-DAG: %[[VAL_1:.*]] = "tosa.reshape"(%arg1) {new_shape = [1, 1, 32, 8]}
+  // CHECK: %[[VAL_2:.*]] = "tosa.select"(%[[VAL_0]], %[[VAL_1]], %arg2)
+  %0 = "tosa.select"(%arg0, %arg1, %arg2) : (tensor<i1>, tensor<32x8xf32>, tensor<1x32x32x8xf32>) -> tensor<1x32x32x8xf32>
+  return %0 : tensor<1x32x32x8xf32>
+}