This paper assesses the contribution of confidence - or sentiment - data in predicting Canadian economic slowdowns. A probit framework is specified and applied to an indicator on the status of the Canadian business cycle produced by the OECD. Explanatory variables include all available Canadian data on sentiment (which arise from four different surveys) as well as various macroeconomic and financial data. The model is estimated via maximum likelihood and sentiment data are introduced either as individual variables, as simple averages (such as confidence indices) and as confidence factors extracted, via principal components' decompositions, from a larger dataset in which all available sentiment data have been collected. Our findings indicate that the full potential of sentiment data for forecasting future business cycles in Canada is attained when all data are used through the use of factor models.