Background: Myocardial scarring is a primary pathogenetic process in nonischemic dilated cardiomyopathy (NIDCM) that is responsible for progressive cardiac remodeling and heart failure, severely impacting the survival of these patients. Although several collagen turnover biomarkers have been associated with myocardial fibrosis, their clinical utility is still limited. Late gadolinium enhancement (LGE) determined by cardiac magnetic resonance imaging (CMR) has become a feasible method to detect myocardial replacement fibrosis. We sought to evaluate the association between collagen turnover biomarkers and replacement myocardial scarring by CMR and, also, to test their ability to predict outcome in conjunction with LGE in patients with NIDCM. Method: We conducted a prospective study on 194 patients (48.7 ± 14.3 years of age; 74% male gender) with NIDCM. The inclusion criteria were similar to those for the definition of NIDCM, performed exclusively by CMR: (1) LV dilation with an LV end-diastolic volume (LVEDV) of over 97 mL/m2; (2) global LV dysfunction, expressed as a decreased LVEF of under 45%. CMR was used to determine the presence and extent of LGE. Several collagen turnover biomarkers were determined at diagnosis, comprising galectin-3 (Gal3), procollagen type I carboxy-terminal pro-peptide (PICP) and N-terminal pro-peptide of procollagen type III (PIIINP). A composite outcome (all-cause mortality, ventricular tachyarrhythmias, heart failure hospitalization) was ascertained over a median of 26 months. Results: Gal3, PICP and PIIINP were considerably increased in those with LGE+ (p < 0.001), also being directly correlated with LGE mass (r2 = 0.42; r2 = 0.44; r2 = 0.31; all p < 0.001). Receiver operating characteristic (ROC) analysis revealed a significant ability to diagnose LGE, with an area under the ROC of 0.816 for Gal3, 0.705 for PICP, and 0.757 for PIIINP (all p < 0.0001). Kaplan–Meier analysis showed that at a threshold of >13.8 ng/dL for Gal3 and >97 ng/dL for PICP, they were able to significantly predict outcome (HR = 2.66, p < 0.001; HR = 1.93, p < 0.002). Of all patients, 17% (n = 33) reached the outcome. In multivariate analysis, after adjustment for covariates, only LGE+ and Gal3+ remained independent predictors for outcome (p = 0.008; p = 0.04). Nonetheless, collagen turnover biomarkers were closely related to HF severity, providing incremental predictive value for severely decreased LVEF of under 30% in patients with NIDCM, beyond that with LGE alone. Conclusions: In patients with NIDCM, circulating collagen turnover biomarkers such as Gal3, PICP and PIIINP are closely related to the presence and extent of LGE and can significantly predict cardiovascular outcome. The joint use of LGE with Gal3 and PICP significantly improved outcome prediction.