Cricket is a highly demanding sport that places the body under a significant amount of strain on a player’s body. Among cricketers, fast bowlers face the maximum plunge due to the physically taxing nature of their skill set. To address these challenges, the proposed model aims to offer a unique view to injury prevention. Unlike the existing solutions which are mostly analytical in their scope and rational in their mannerism, the proposed model strives to provide a predictive analysis that is intelligent in its behavior. The presented model captures the posture of the bowler at their landing stage. It analyzes his/her actions for potential injury scares. If the inference of the analysis labels the test action as injury-prone, it is moved to the next stage which is reverse image search. Here, the model showcases its predictive prowess and predicts an action that is less prone to injuries and can be attained by making the minimum number of adjustments to the original action.