Memes have proliferated through digital channels, sharing humor, culture-laden references, and emotions across social media. MemeForge is an online application that makes this work automated and personalized for the user. Equipped with emotion detection algorithms that integrate with a simple user interface, it involves picture uploading and text entry to make memes. A Convolutional Neural Network (CNN) for MemeForge infers possible emotions from facial expressions and visual elements, ensuring that the memes are contextually related to the user's emotional state. MemeForge features an additional input type that collects image entry using NLP in addition to the other types for meme generation reflective of the emotional tone in user-submitted text. In this way, the app parameters across visual and textual input guarantee granularity for a deep and engaging user experience. MemeForge connects users to the Imgflip API for popular memes available to be used based on their perceived emotional detection, encouraging the uplifting users’ creativity in several dimensions. Real-Time processing which could be inspired from language translation systems would help MemeForge in giving almost instant feedback while creating memes. The application develops by using Optical Character Recognition (OCR) for text extraction from images and makes possible the captioning using embedded text. Integrating emotion detection, NLP, OCR, and real-time processing redefines MemeForge into an arsenal for creativity within the digital content sphere and the way users represent their ideas of emotions and humor through memes. This paper covers all the technologies supporting MemeForge, evaluates the features that it offers, and discusses the possible implications it can have in the digital communication arena in cultural expression.