Selection of an appropriate sampling strategy is an important prerequisite to establish core collections of appropriate size in order to adequately represent the genetic spectrum and maximally capture the genetic diversity in available crop collections. We developed a simulation approach to identify an optimal sampling strategy and core-collection size, using isozyme data from a CIP germplasm collection on an Andean tetraploid potato. Five sampling strategies, constant (C), proportional (P), logarithmic (L), square-root (S) and random (R), were tested on isozyme data from 9,396 Andean tetraploid potato accessions characterized for nine isozyme loci having a total of 38 alleles. The 9,396 accessions, though comprising 2,379 morphologically distinct accessions, were found to represent 1,910 genetically distinct groups of accessions for the nine isozyme loci using a sort-and-duplicate-search algorithm. From each group, one accession was randomly selected to form a genetically refined entire collection (GREC) of size 1,910. The GREC was used to test the five sampling strategies. To assess the behavior of the results in repeated sampling, k = 1,500 and 5,000 independent random samples (without replacement) of admissible sizes n = 50(50)1,000 for each strategy were drawn from GREC. Allele frequencies (AF) for the 38 alleles and locus heterozygosity (LH) for the nine loci were estimated for each sample. The goodness of fit of samples AF and LH with those from GREC was tested using the χ2 test. A core collection of size n = 600, selected using either the P or the R sampling strategy, was found adequately to represent the GREC for both AF and LH. As similar results were obtained at k = 1,500 and 5,000, it seems adequate to draw 1,500 independent random samples of different sizes to test the behavior of different sampling strategies in order to identify an appropriate sampling approach, as well as to determine an optimal core collection size.