In an era where cyber threats are increasing, security with a strong password is of greatest importance. This paper presents a unique password prediction system that utilizes the power of neural networks to create strong, unique passwords and accurately assess their resistance to cracking attempts. Our system uses long-term and short-term memory networks for password generation. User-Defined Complexity… -Criterion Consideration for energy estimation. We use architecture Hybrid Convolutional Neural Network (CNN) and LSTM, which provide real-time feedback on password security. The system incorporates temperature sampling for controlled randomization in password generation. And use complexity-based character weighting to increase the strength of the password. This allows communication with cloud services. This makes it easier for users to generate and evaluate passwords in real time through an AI-powered module. Additionally, users can customize password generation parameters using the web application. The brief covers various aspects of the system, including requirements. Integration of technology prototyping development steps and architecture. This password system aims to enhance cyber security practices. Reduce the risk of attacks and improve password management across digital environments. Our project combines a cutting-edge approach using advanced machine learning techniques and cloud solutions to revolutionize password security. Real-time energy estimation is provided through the CNN-LSTM model, which is seamlessly integrated into the cloud platform. This cloud system plays an important role in managing data processing. Creating a password and sharing of safety information in addition, the complex dynamic wiring strategy.