Inter-well connectivity (IWC) is a key factor for the successful design and operation of waterflooding projects. Thus, connectivity estimation methods such as the Capacitance-Resistance Model (CRM) are continually being improved and developed. The CRM utilizes the injection and production data as input to quantify IWC information through a connectivity parameter (λ). Proposed in 2006, the CRM has been adapted several times to better perform in challenging exploitation projects such as heavy oil waterflooding. Nonetheless, CRM analysis in heavy oil reservoirs yields highly variable λ values during early times. Such a variation and inconsistency make it difficult to readily determine IWC. This research work proposes two novel approaches to improve the CRM analysis by evaluating the uncertainty in the IWC estimates, especially at the early production stage. In the first approach, data generated from reservoir simulations provide input for the CRM to estimate IWC for each injection-production well pair. The objective is to define an equation relating production data and λ behavior patterns for different high mobility ratio cases. The proposed formulation yields acceptable IWC results in homogeneous reservoir cases and provides insight into heterogeneous reservoir evaluations. For the second approach, the analogous behavior of heat conduction and pressure transients is used to complement the CRM analysis. Previous studies suggest that, besides inter-well distance (IWD), IWC estimation might be influenced by injection rate frequency (ω_a) and medium hydraulic diffusivity (D). Sensitivities of those parameters were carried out to determine their effect on IWC. As a result, applying the periodic line source solution (PLSS) for heat conduction, ω_a, D and IWD can all be considered for IWC estimation, and their effects quantified. The PLSS analysis also offered an improvement on a previously proposed method to estimate CRM connectivity prediction errors. The modification includes the effects of ω_a and IWD to provide a better error predictor. A field-case example of the modified method shows the impact of IWD and ω_a in the deviation of CRM- λs. A relevant benefit of this method is its applicability to a wide range of reservoir conditions and fluid types, at any field development stage.