In this work we are interested in quantifying the conductivity and epicardial potential boundary data uncertainties for the forward problem of electrocardiography (ECG). Indeed these input data are very important for the computation of the torso potential and consequently for the computation of the ECG. We use a stochastic approach for two dimensional torso geometry. We attribute probability density functions for the various source of randomness, and apply stochastic finite elements based on generalized polynomial chaos method. This work is the first step in order to quantify the uncertainties in inverse problem, which the goal is to complete the epicardial data. The efficiency of this approach to solve the forward ECG problem and the usability to quantify the effect of organs conductivity and epicardial boundary data uncertainties in the torso are demonstrated through a number of numerical simulations on a 2D computational mesh of the torso geometry.