Recent studies indicate that zinc alloys are preferred in biodegradable metal materials owing to their unique biodegradability and biocompatibility. However, their mechanical properties are relatively insufficient; thus, it is crucial to design zinc alloys that meet the mechanical performance implantation standards required for application in biomedicine. The traditional alloy design method depends on experience and trial and error for low efficiency and high cost. In recent years, the rapid development of artificial intelligence has provided new tools and methods for material science. Machine learning (ML), a subset of artificial intelligence, offers new ideas for material design and prediction. This study obtained the mechanical property data of the Zn Mg Mn alloy through experimental investigation and literature review. A performance-oriented ML model was used to predict the compressive yield strength (CYS) and hardness of the Zn Mg Mn alloy, considering various element types and contents and different alloy preparation processes. Furthermore, the influence of the element types and contents on the microstructure and macroscopic mechanical properties of the material was explored. This model used an existing dataset and compared it with seven different ML algorithms to determine that the k-nearest neighbor algorithm has the best predictive ability, exceeding 90%. To further validate the accuracy of the model prediction, a random method was used to select data beyond the dataset for comparative analysis with the model results. Simultaneously, the Shapley Additive exPlanations was applied to quantitatively examine the correlation between the two alloying elements, the preparation process, the CYS, and the hardness in the Zn Mg Mn alloy. The Mg element was determined to significantly impact the alloy’s CYS and hardness. Finally, the influence of individual elements on the mechanical properties of the materials was analyzed through microstructure characterization; the results showed that the formation of new phases (Mg₂Zn₁₁ and MgZn₁₃) due to adding these elements significantly affected the mechanical properties. Based on the research results, this study proposed a composition ratio range for the Zn Mg Mn alloy to satisfy the mechanical performance standards required for medical implant materials. When Mg is between 2.25% and 2.50% (mass fraction, the same below) and Mn is between 2.50% and 3.50%, the CYS and hardness of the alloy comply with the implant standards.