diff --git a/Example/Podfile.lock b/Example/Podfile.lock
index b438a203..a7c06e2b 100644
--- a/Example/Podfile.lock
+++ b/Example/Podfile.lock
@@ -43,7 +43,7 @@ SPEC CHECKSUMS:
   lottie-ios: fcb5e73e17ba4c983140b7d21095c834b3087418
   netfox: 9d5cc727fe7576c4c7688a2504618a156b7d44b7
   Sentry: 96ae1dcdf01a644bc3a3b1dc279cecaf48a833fb
-  SmileID: 8d3a64e845a5fb82239516def978391d4d814c9e
+  SmileID: 97a579344f72c543d6b3aa8b56722d05646d2023
   SwiftLint: 3fe909719babe5537c552ee8181c0031392be933
   ZIPFoundation: b8c29ea7ae353b309bc810586181fd073cb3312c
 
diff --git a/Sources/SmileID/Classes/FaceDetector/FaceDetectorV2.swift b/Sources/SmileID/Classes/FaceDetector/FaceDetectorV2.swift
index 99ef6268..764b60da 100644
--- a/Sources/SmileID/Classes/FaceDetector/FaceDetectorV2.swift
+++ b/Sources/SmileID/Classes/FaceDetector/FaceDetectorV2.swift
@@ -8,6 +8,7 @@ protocol FaceDetectorDelegate: NSObjectProtocol {
 }
 
 class FaceDetectorV2: NSObject {
+    private let cropSize = (width: 120, height: 120)
     private let faceMovementThreshold: CGFloat = 0.15
 
     var sequenceHandler = VNSequenceRequestHandler()
@@ -48,7 +49,7 @@ class FaceDetectorV2: NSObject {
             guard let croppedImage = try cropToFace(image: image) else {
                 return
             }
-            guard let convertedImage = croppedImage.pixelBuffer(width: 120, height: 120) else {
+            guard let convertedImage = croppedImage.pixelBuffer(width: cropSize.width, height: cropSize.height) else {
                 return
             }
             selfieQualityRequest(imageBuffer: convertedImage)
diff --git a/Sources/SmileID/Classes/FaceDetector/ImageClassifier.swift b/Sources/SmileID/Classes/FaceDetector/ImageClassifier.swift
deleted file mode 100644
index 4117ab05..00000000
--- a/Sources/SmileID/Classes/FaceDetector/ImageClassifier.swift
+++ /dev/null
@@ -1,117 +0,0 @@
-import CoreML
-import Vision
-
-/// An enum representing possible errors during image classification
-enum ImageClassifierError: Error {
-    case preprocessingFailed
-    case classificationFailed
-    case invalidOutputFormat
-    case imageConversionFailed
-    case faceCroppingFailed
-}
-
-/// A structure representing the image quality check result
-struct ImageQualityResult {
-    let passed: Bool
-    let confidence: Float
-
-    var description: String {
-        return passed ? "Passed" : "Failed"
-    }
-}
-
-/// A class that performs image classification to determine selfie quality using a Core ML Model
-class ModelImageClassifier {
-    let cropSize = (width: 120, height: 120)
-
-    init() {}
-
-    /// Classifies an image using the Core ML Model
-    /// - Parameter image: The input image as a UIImage
-    /// - Returns: A result containing classifiction confidence.
-    func classify(imageBuffer: CVPixelBuffer) async throws -> ImageQualityResult {
-        do {
-            guard let image = UIImage(pixelBuffer: imageBuffer) else {
-                throw ImageClassifierError.preprocessingFailed
-            }
-            let croppedImage = try await cropToFace(image: image)
-            guard let convertedImage = croppedImage.pixelBuffer(width: cropSize.width, height: cropSize.height) else {
-                throw ImageClassifierError.preprocessingFailed
-            }
-            return try performClassification(imageBuffer: convertedImage)
-        } catch {
-            throw error
-        }
-    }
-
-    /// Crops the input image to the region of the first face in the image.
-    /// - Parameter image: The original input image that should have a face.
-    /// - Returns: A cropped image of the detected face in the input image.
-    private func cropToFace(image: UIImage) async throws -> UIImage {
-        guard let cgImage = image.cgImage else {
-            throw ImageClassifierError.faceCroppingFailed
-        }
-
-        let request = VNDetectFaceRectanglesRequest()
-        let handler = VNImageRequestHandler(cgImage: cgImage, options: [:])
-
-        try handler.perform([request])
-
-        guard let results = request.results,
-              let face = results.first else {
-            throw ImageClassifierError.faceCroppingFailed
-        }
-
-        let boundingBox = face.boundingBox
-
-        let size = CGSize(
-            width: boundingBox.width * image.size.width,
-            height: boundingBox.height * image.size.height
-        )
-        let origin = CGPoint(
-            x: boundingBox.minX * image.size.width,
-            y: (1 - boundingBox.minY) * image.size.height - size.height
-        )
-
-        let faceRect = CGRect(origin: origin, size: size)
-
-        guard let croppedImage = cgImage.cropping(to: faceRect) else {
-            throw ImageClassifierError.faceCroppingFailed
-        }
-
-        return UIImage(cgImage: croppedImage)
-    }
-
-    /// Performs the actual classification using the `ImageQualityCP20` model
-    /// - Parameter mlMultiArray: The processed input image as a MultiArray
-    /// - Returns: The ImageQualityResult
-    private func performClassification(imageBuffer: CVPixelBuffer) throws -> ImageQualityResult {
-        let modelConfiguration = MLModelConfiguration()
-        let model = try SelfieQualityDetector(configuration: modelConfiguration)
-
-        let input = SelfieQualityDetectorInput(conv2d_193_input: imageBuffer)
-
-        let prediction = try model.prediction(input: input)
-        let output = prediction.Identity
-        return try processModelOuput(output)
-    }
-
-    /// Processes the model's output to determine the final classification
-    /// - Parameter output: The MLMultiArray output from the model
-    /// - Returns: The ImageQualityResult
-    private func processModelOuput(_ output: MLMultiArray) throws -> ImageQualityResult {
-        guard output.shape.count == 2,
-              output.shape[0] == 1,
-              output.shape[1] == 2 else {
-            throw ImageClassifierError.invalidOutputFormat
-        }
-
-        let failScore = output[0].floatValue
-        let passScore = output[1].floatValue
-
-        let passed = passScore > failScore
-        let confidence = passed ? passScore : failScore
-
-        return ImageQualityResult(passed: passed, confidence: confidence)
-    }
-}