Cancer is the result of several genetic alterations that overrule a cell’s protection mechanisms against unscheduled proliferation (Hanahan & Weinberg, 2000). As the vast majority of human tumours show chromosomal instability (CIN), CIN is believed to be an important driver and facilitator of oncogenic transformation. CIN can result in structural abnormalities such as focal deletions, amplifications or translocations (structural CIN). Alternatively, CIN causes numerical abnormalities (i.e. aneuploidy) with cells showing high rates of losses and gains of whole chromosomes leading to dramatic karyotypic variability between cells. Whereas alterations to single or small groups of oncogenes/ tumour suppressor genes can explain the malignant effect of structural CIN, the cancerous effect of numerical CIN is mostly attributed to the loss of heterozygosity (LOH) of tumour suppressor genes (Jallepalli & Lengauer, 2001, Kops et al., 2005). Structural and numerical CIN often coincide in tumours and numerical CIN can in fact provoke structural CIN as well (Janssen et al., 2011). Although CIN appears to be a potent driver of genomic reorganization, it comes at cost for cells. For instance, numerical CIN in tissue culture cells kills cells within six generations (Kops et al., 2004). Furthermore, in depth analysis of aneuploid yeast strains and mouse embryonic fibroblasts (MEFs) carrying an extra chromosome revealed that aneuploidy slows cell proliferation down and deregulates the metabolic homeostasis (Torres et al., 2007, Williams et al., 2008). However, as the majority of human tumours are aneuploid, cancer cells must have found a way to circumvent the detrimental consequences of CIN. This chapter reviews several mechanisms that can drive numerical CIN and discusses several of the mouse models that were engineered to mimic these conditions with the aim to study the in vivo consequences of numerical CIN.