D-LIM (Direct-Latent Interpretable Model) is a neural network that enhances genotype-fitness mapping by combining interpretability with predictive accuracy. It assumes independent phenotypic influences of genes on fitness, leading to advanced accuracy and insights into phenotype analysis and epistasis. The model includes an extrapolation method for better understanding of genetic interactions and integrates multiple data sources to improve performance in low-data biological research.