X.509 certificates enable to affirm the distinguishing proof of the parties involved in the communication. As of now, majority of individuals and communities are using X.509 certificates to demonstrate their ID during on-line exchanges, so the unwavering quality and risk level of these certificates come into a question. Hence, we have proposed a framework which assesses risk associated with X.509 Certificates with the help of certain trust criteria and characteristics. For evaluating risk related with certificate we use classification Technique with machine learning algorithm, which categorizes risk of certificate in three levels-High Risk, Medium Risk and Low risk. Our system is useful to find out risk associated with certificate while user carries out important transactions. User needs to input the certificate and system will provide risk associated with that certificate and if it is a high risk or medium risk certificate it will mention due to which parameter it bears risk. Our framework has application in browser-server communication and detecting phishing websites which have Https URLs.