Genotype-based prediction of an organism’s phenotype can be facilitated by the development of a gene-based crop model. Current crop models comprise a complex set of interrelated mathematical functions that describe growth and development of a crop as it interacts with the environment, but demand calibration with each genotype (cultivar). If calibration yields a set of cultivar-specific model parameters, then it follows that they contain genetic information. Our aim is to extract this genetic information and to turn the model parameters into mathematical functions of the genotype. Towards this objective, we have carried out genome wide search for QTLs relevant to the crop model by using a recombinant inbred family (180 lines) generated from a cross between an Andean (Calima) and a Mesoamerican (Jamapa) common bean accessions. QTLs have been identified via conventional and Functional Mapping (FM) approaches. Dynamic traits are usually controlled by multiple genes, each with distinct chronological expression patterns. FM provides the mathematical framework to identify these genes and estimate their effects during trait development. A dense linkage map and phenotype data of the RIL family, consisting of growth measurements and developmental indexing, were used for QTL analysis. We have identified QTLs controlling time to first flower, seed weight, node number on main stem and leaf area. In addition, QTL analysis using estimated genotype specific parameters from the RILs has also been carried out. We expect that results from parallel QTL mapping analyses will lead to the development of the gene-based crop model.