Dental care primarily focuses mainly on natural aesthetic appearance of the teeth and their through treatment to achieve patients’ satisfaction. However, this treatment is affected by various technical & environmental factors. Different types of light sources in clinic and labs can causse a issue of metamerism. Traditionally, dentist uses physical color charts to match the color or shade of teeth with dental material and this method does not work well always. To help, this study proposes a application called “Smile Spectrum” that automatically reduces the effect of metamerism and find the exact color of teeth. This application was built using Android Studio and Python and it uses machine learning techniques like Support Vector Machine (SVM) & Random Forest to identify exact tooth shade of a patient. We have trained the model using database from Kaggle which include color categories A, B, C & D. Our android-based app captures photo with the help of smartphone camera and uses these images to predict the most matching tooth shade group. Experimental studies were conducted using SVM & random forest algorithms on the dataset created using Kaggle data. Our findings demonstrated that the limitation of traditional method of color matching can be overcome by this app using machine learning techniques and metamerism can be reduced. This approach makes tooth shade matching more consistent, faster & less dependent on physical shade charts. In routine dental practice, this app improves reliability and ease of tooth shade selection.