With the rapid growth of the automotive industry, passenger cars are becoming increasingly common in large cities, making it harder to find available parking spaces. Parking lots represent a heavily used service, with significant investments made each year. Managing these parking facilities can be costly and complex, particularly in large-scale areas such as airports or shopping centers. Traffic congestion in parking areas is a growing issue, as the number of vehicles rises much faster than the availability of parking spaces. The proposed model identifies all available parking slots in a given area and analyzes data to determine whether each slot is vacant or occupied, providing real-time information on available spaces. Our system is designed to detect the parking slot availability by using CNN, Random Forest and SVM. These methods were evaluated using precision, recall and accuracy. The results obtained were tested, SVM accuracy is 98% which is promising in finding the vacant slots of the parking area.